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  • 1.
    Jamil, Mohammad Newaj
    et al.
    Department of Computer Science and Engineering, University of Chittagong, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Belief Rule Based Expert System for Evaluating Technological Innovation Capability of High-Tech Firms Under Uncertainty2019In: Proceedings of the Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV), IEEE, 2019Conference paper (Refereed)
    Abstract [en]

    Technological innovation capability (TIC) is a complicated and subtle concept which is based on multiple quantitative and qualitative criteria. The cores of a firm’s long-term competitive dominance are defined by technological innovation capability which is the incentive for a firm’s innovation. Various types of uncertainty can be noticed while considering multiple criteria for evaluating TIC. In order to evaluate TIC in a reliable way, a Belief Rule Base (BRB) Expert System can be used to handle both quantitative and qualitative data and their associated uncertainties. In this paper, a RESTful API-based BRB expert system is introduced to evaluate technological innovation capability by taking uncertainties into consideration. This expert system will facilitate firms’ managers to obtain a recapitulation of the TIC evaluation. It will help them to take essential steps to ensure corporate survival and strengthen their weak capabilities continuously to facilitate a competitive advantage. Other users can also use this API to apply BRB for a different domain. However, a comparison between the knowledge-driven approach (BRBES) and several data-driven models has been performed to find out the reliability in evaluating TIC. The result shows that the outcome of BRBES is better than other data-driven approaches.

  • 2.
    Akter, Shamima
    et al.
    International Islamic University, Chittagong, Bangladesh.
    Nahar, Nazmun
    University of Chittagong, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A New Crossover Technique to Improve Genetic Algorithm and Its Application to TSP2019In: Proceedings of 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE), IEEE, 2019, article id 18566123Conference paper (Refereed)
    Abstract [en]

    Optimization problem like Travelling Salesman Problem (TSP) can be solved by applying Genetic Algorithm (GA) to obtain perfect approximation in time. In addition, TSP is considered as a NP-hard problem as well as an optimal minimization problem. Selection, crossover and mutation are the three main operators of GA. The algorithm is usually employed to find the optimal minimum total distance to visit all the nodes in a TSP. Therefore, the research presents a new crossover operator for TSP, allowing the further minimization of the total distance. The proposed crossover operator consists of two crossover point selection and new offspring creation by performing cost comparison. The computational results as well as the comparison with available well-developed crossover operators are also presented. It has been found that the new crossover operator produces better results than that of other cross-over operators.

  • 3.
    Hossain, Mohammad Shahadat
    et al.
    University of Chittagong, Bangladesh.
    Sultana, Zinnia
    International Islamic University Chittagong, Bangladesh.
    Nahar, Lutfun
    International Islamic University Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    An Intelligent System to Diagnose Chikungunya under Uncertainty2019In: Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, ISSN 2093-5374, E-ISSN 2093-5382, Vol. 10, no 2, p. 37-54Article in journal (Refereed)
    Abstract [en]

    Chikungunya is a virus-related disease, bring about by the virus called CHIKV that spreads throughmosquito biting. This virus first found in Tanzania, while blood from patients was isolated. Thecommon signs and symptoms, associated with Chikungunya are considered as fever, joint swelling,joint pain, muscle pain and headache. The examination of these signs and symptoms by the physician constitutes the typical preliminary diagnosis of this disease. However, the physician is unable tomeasure them with accuracy. Therefore, the preliminary diagnosis in most of the cases could sufferfrom inaccuracy, which leads to wrong treatment. Hence, this paper introduces the design and implementation of a belief rule based expert system (BRBES) which is capable to represent uncertainknowledge as well as inference under uncertainty. Here, the knowledge is illustrated by employing belief rule base while deduction is carried out by evidential reasoning. The real patient data of250 have been considered to demonstrate the accuracy and the robustness of the expert system. Acomparison has been performed with the results of BRBES and Fuzzy Logic Based Expert System(FLBES) as well as with the expert judgment. Furthermore, the result of BRBES has been contrastedwith various data-driven machine learning approaches, including ANN (Artificial Neural networks)and SVM (Support Vector Machine). The reliability of BRBESs was found better than those of datadriven machine learning approaches. Therefore, the BRBES presented in this paper could enable thephysician to conduct the analysis of Chikungunya more accurately.

  • 4.
    Chowdhury, Rumman Rashid
    et al.
    Department of Computer Science and Engineering, University of Chittagong, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Sazzad
    Department of Computer Science and Engineering, University of Liberal Arts Bangladesh, Dhaka, Bangladesh.
    Bangla Handwritten Character Recognition using Convolutional Neural Network with Data Augmentation2019In: Proceedings of the Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV), 2019Conference paper (Refereed)
    Abstract [en]

    This paper proposes a process of Handwritten Character Recognition to recognize and convert images of individual Bangla handwritten characters into electronically editable format, which will create opportunities for further research and can also have various practical applications. The dataset used in this experiment is the BanglaLekha-Isolated dataset [1]. Using Convolutional Neural Network, this model achieves 91.81% accuracy on the alphabets (50 character classes) on the base dataset, and after expanding the number of images to 200,000 using data augmentation, the accuracy achieved on the test set is 95.25%. The model was hosted on a web server for the ease of testing and interaction with the model. Furthermore, a comparison with other machine learning approaches is presented.

  • 5.
    Kor, Ah-Lian
    et al.
    Leeds Beckett University.
    Rondeau, Eric
    University of Lorraine, Nancy, France.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Porras, Jari
    Lappeenranta University of Technology, Finland.
    Georges, Jean-Philippe
    University of Lorraine, Nance, France.
    Education in Green ICT and Control of Smart Systems: A First Hand Experience from the International PERCCOM Masters Programme2019In: Proceedings of the 12th International Federation of Automatic Control Symposium on Advances in Control Education (IFAC-ACE 2019), 2019Conference paper (Refereed)
    Abstract [en]

    PERCCOM (PERvasive Computing and COMmunications in sustainable development) Masters is the first innovative international programme in Green ICT for educating and equipping new IT engineers with Green IT skills for sustainable digital applications design and implementation. After five years of running the PERCCOM programme, this paper provides an assessment of skills and employability in the context of Green jobs and skills. The paper ends with a list of recommendations for the development of environment related education curricula.

  • 6.
    Poirot, Valentin
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Ericson, Mårten
    Ericsson Research, Luleå, Sweden.
    Nordberg, Mats
    Ericsson Research, Luleå, Sweden.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Energy efficient multi-connectivity algorithms for ultra-dense 5G networks2019In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, p. 1-16Article in journal (Refereed)
    Abstract [en]

    Two radio air interfaces, Evolved-LTE and New Radio, coexist in new 5G systems. New Radio operates in the millimeter band and provides a better bandwidth, but the higher frequencies also imply worse radio conditions. Multi-connectivity, a feature of 5G that allows users to connect to more than one base station simultaneously, can offer the advantages of both interfaces. In this paper, we investigate how multi-connectivity can improve user reliability and the system’s energy efficiency. Five algorithms for secondary cell association are presented and evaluated. We show a decrease in the radio link failure rate of up to 50% at high speeds and improvements of the energy efficiency of up to 20% at low speeds.

  • 7.
    Uddin Ahmed, Tawsin
    et al.
    Department of Computer Science and Engineering, University of Chittagong, Bangladesh.
    Hossain, Sazzad
    Department of Computer Science and Engineering, University of Liberal Arts Bangladesh, Dhaka, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Facial Expression Recognition using Convolutional Neural Network with Data Augmentation2019In: Proceedings of the Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV), 2019Conference paper (Refereed)
    Abstract [en]

    Detecting emotion from facial expression has become an urgent need because of its immense applications in artificial intelligence such as human-computer collaboration, data-driven animation, human-robot communication etc. Since it is a demanding and interesting problem in computer vision, several works had been conducted regarding this topic. The objective of this research is to develop a facial expression recognition system based on convolutional neural network with data augmentation. This approach enables to classify seven basic emotions consist of angry, disgust, fear, happy, neutral, sad and surprise from image data. Convolutional neural network with data augmentation leads to higher validation accuracy than the other existing models (which is 96.24%) as well as helps to overcome their limitations.

  • 8.
    Islam, Raihan Ul
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Centre for Critical Infrastructure and Societal Security.
    Hossain, Mohammad Shahadat
    Department of Computer Science and Engineering, University of Chittagong.
    Network Intelligence for Enhanced Multi-Access Edge Computing (MEC) in 5G2019Conference paper (Other academic)
    Abstract [en]

    5G networks will enable people and machines to communicate at high speeds and very low latencies, in a reliable way. This opens up opportunities for totally new usage patterns and the fully connected Industry 4.0-enabled enterprise covering the entire value chain from design, production, deployment, to usage of products. 5G will be rolled out across the whole world, including Sweden where the first 5G test network was launched late 2018. One important new feature in 5G is the emerging edge computing capabilities, where users can easily offload computational tasks to the network’s edge very close to the user. At the same time, computational tasks traditionally performed in central nodes can be offloaded from remotely located data centres to the network’s edge. Multi-access Edge Computing (MEC) is a promising network architecture delivering solutions along these lines offering a platform for applications with requirements on low latencies and high reliability. This paper targets this environment with a novel Belief-rule-based (BRB) unsupervised learning algorithm for clustering helping 5G applications to take intelligent decisions on software deployment. The scenarios consist of different combinations of numbers of users and connections and mobility patterns. The target environment is built up using a three-tier structure with a container-based solution where software components can easily be spread around the network.

  • 9.
    Andersson, Karl
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    You, Ilsun
    Soonchunhyang University, Asan, Republic of Korea.
    Rahmani, Rahim
    Stockholm University, Stockholm, Sweden.
    Sharma, Vishal
    Soonchunhyang University, Asan, Republic of Korea.
    Secure Computation on 4G/5G Enabled Internet-of-Things2019In: Wireless Communications & Mobile Computing, ISSN 1530-8669, E-ISSN 1530-8677, Vol. 2019, article id 3978193Article in journal (Refereed)
    Abstract [en]

    The rapid development of Internet-of-Things (IoT) techniques in 4G/5G deployments is witnessing the generation of massive amounts of data which are collected, stored, processed, and presented in an easily interpretable form. Analysis of IoT data helps provide smart services such as smart homes, smart energy, smart health, and smart environments through 4G and 5G technologies. At the same time, the threat of the cyberattacks and issues with mobile internet security is becoming increasingly severe, which introduces new challenges for the security of IoT systems and applications and the privacy of individuals thereby. Protecting IoT data privacy while enabling data availability is an urgent but difficult task.

    Data privacy in a distributed environment like IoT can be attained through secure multiparty computation. An emerging area of potential applications for secure computation is to address privacy concerns in data aggregation and analysis to match the explosive growth of the amount of IoT data. However, the inherent complexity of IoT systems really complicates the design and deployment of efficient, interoperable, and scalable secure computation mechanisms. As a result, there is an increasing demand for the development of new secure computation methods and tools which can fill in the gap between security and practical usage in IoT.

    The scope of this special issue is in line with recent contributions from academia and industry on the recent activities that tackle the technical challenges making computing secure on 4G/5G enabled Internet-of-Things. For the current issue, we are pleased to introduce a collection of papers covering a range of topics such as securely verifiable remote erasure schemes, multiuser identification algorithms, privacy-preserving shared storage, situational aware threat assessment, authorized client-side deduplication in cloud storage, radio environment map construction, analysis of the vulnerabilities of connected car environments, combat pollution attacks in 5G multihop networks, automatically traceback RDP-based targeted ransomware attacks, multiresolution face recognition through virtual faces generation, anonymous communication via anonymous identity-based encryption, and Secure Storage and Retrieval of IoT Data.

  • 10.
    Islam, Md. Zahirul
    et al.
    Department of Computer Science and Engineering University of Chittagong, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Static Hand Gesture Recognition using Convolutional Neural Network with Data Augmentation2019In: Proceedings of the Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV), IEEE, 2019Conference paper (Refereed)
    Abstract [en]

    Computer is a part and parcel in our day to day life and used in various fields. The interaction of human and computer is accomplished by traditional input devices like mouse, keyboard etc. Hand gestures can be a useful medium of human-computer interaction and can make the interaction easier. Gestures vary in orientation and shape from person to person. So, non-linearity exists in this problem. Recent research has proved the supremacy of Convolutional Neural Network (CNN) for image representation and classification. Since, CNN can learn complex and non-linear relationships among images, in this paper, a static hand gesture recognition method using CNN was proposed. Data augmentation like re-scaling, zooming, shearing, rotation, width and height shifting was applied to the dataset. The model was trained on 8000 images and tested on 1600 images which were divided into 10 classes. The model with augmented data achieved accuracy 97.12% which is nearly 4% higher than the model without augmentation (92.87%).

  • 11.
    Hossain, Mohammad Shahadat
    et al.
    University of Chittagong, Bangladesh.
    Al Hasan, Abdullah
    University of Chittagong, Bangladesh.
    Guha, Sunanda
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Belief Rule Based Expert System to Predict Earthquake under Uncertainty2018In: Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, ISSN 2093-5374, E-ISSN 2093-5382, Vol. 9, no 2, p. 26-41Article in journal (Refereed)
    Abstract [en]

    The impact of earthquake is devastating, which has the capability to stop the socio-economic activities of a region within a short span of time. Therefore, an earlier prediction of earthquake could play an important role to save human lives as well as socio-economic activities. The signs of animal behavior along with environmental and chemical changes in nature could be considered as a way to predict the earthquake. These factors cannot be determined accurately because of the presence of different categories of uncertainties. Therefore, this article presents a belief rule based expert system (BRBES) which has the capability to predict earthquake under uncertainty. Historical data of various earthquakes of the world with specific reference to animal behavior as well as environmental and chemical changes have been considered in validating the BRBES. The reliability of our proposed BRBES’s output is measured in comparison with Fuzzy Logic Based Expert System (FLBES) and Artificial Neural Networks (ANN) based system, whereas our BRBES’s results are found more reliable than that of FLBES and ANN. Therefore, this BRBES can be considered to predict the occurrence of an earthquake in a region by taking account of the data, related to the animal, environmental and chemical changes.

  • 12.
    Monrat, Ahmed Afif
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Belief Rule Based Flood Risk Assessment Expert System using Real Time Sensor Data Streaming2018In: Proveedings of the 43nd IEEE Conference on Local Computer Networks Workshops (LCN Workshops), Piscataway, NJ: IEEE Computer Society, 2018, p. 8-45Conference paper (Refereed)
    Abstract [en]

    Among the various natural calamities, flood is considered one of the most catastrophic natural hazards, which has a significant impact on the socio-economic lifeline of a country. The Assessment of flood risks facilitates taking appropriate measures to reduce the consequences of flooding. The flood risk assessment requires Big data which are coming from different sources, such as sensors, social media, and organizations. However, these data sources contain various types of uncertainties because of the presence of incomplete and inaccurate information. This paper presents a Belief rule-based expert system (BRBES) which is developed in Big data platform to assess flood risk in real time. The system processes extremely large dataset by integrating BRBES with Apache Spark while a web-based interface has developed allowing the visualization of flood risk in real time. Since the integrated BRBES employs knowledge driven learning mechanism, it has been compared with other data-driven learning mechanisms to determine the reliability in assessing flood risk. The integrated BRBES produces reliable results in comparison to other data-driven approaches. Data for the expert system has been collected by considering different case study areas of Bangladesh to validate the system.

  • 13.
    Hossain, Mohammad Shahadat
    et al.
    University of Chittagong, Bangladesh.
    Rahaman, Saifur
    International Islamic University Chittagong.
    Mustafa, Rashed
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A belief rule-based expert system to assess suspicion of acute coronary syndrome (ACS) under uncertainty2018In: Soft Computing - A Fusion of Foundations, Methodologies and Applications, ISSN 1432-7643, E-ISSN 1433-7479, Vol. 22, no 22, p. 7571-7586Article in journal (Refereed)
    Abstract [en]

    Acute coronary syndrome (ACS) is responsible for the obstruction of coronary arteries, resulting in the loss of lives. The onset of ACS can be determined by looking at the various signs and symptoms of a patient. However, the accuracy of ACS determination is often put into question since there exist different types of uncertainties with the signs and symptoms. Belief rule-based expert systems (BRBESs) are widely used to capture uncertain knowledge and to accomplish the task of reasoning under uncertainty by employing belief rule base and evidential reasoning. This article presents the process of developing a BRBES to determine ACS predictability. The BRBES has been validated against the data of 250 patients suffering from chest pain. It is noticed that the outputs created from the BRBES are more dependable than that of the opinion of cardiologists as well as other two expert system tools, namely artificial neural networks and support vector machine. Hence, it can be argued that the BRBES is capable of playing an important role in decision making as well as in avoiding costly laboratory investigations. A procedure to train the system, allowing its enhancement of performance, is also presented.

  • 14.
    Islam, Raihan Ul
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    Department of Computer Science and Engineering, University of Chittagong, Chittagong 4331, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A novel anomaly detection algorithm for sensor data under uncertainty2018In: Soft Computing - A Fusion of Foundations, Methodologies and Applications, ISSN 1432-7643, E-ISSN 1433-7479, Vol. 22, no 5, p. 1623-1639Article in journal (Refereed)
    Abstract [en]

    It is an era of Internet of Things, where various types of sensors, especially wireless, are widely used to collect huge amount of data to feed various systems such as surveillance, environmental monitoring, and disaster management. In these systems, wireless sensors are deployed to make decisions or to predict an event in a real-time basis. However, the accuracy of such decisions or predictions depends upon the reliability of the sensor data. Unfortunately, erroneous data are received from the sensors. Consequently, it hampers the appropriate operations of the mentioned systems, especially in making decisions and prediction. Therefore, the detection of anomaly that exists with the sensor data drew significant attention and hence, it needs to be filtered before feeding a system to increase its reliability in making decisions or prediction. There exists various sensor anomaly detection algorithms, but few of them are able to address the uncertain phenomenon, associated with the sensor data. If these uncertain phenomena cannot be addressed by the algorithms, the filtered data into the system will not be able to increase the reliability of the decision-making process. These uncertainties may be due to the incompleteness, ignorance, vagueness, imprecision and ambiguity. Therefore, in this paper we propose a new belief-rule-based association rule (BRBAR) with the ability to handle the various types of uncertainties as mentioned.The reliability of this novel algorithm has been compared with other existing anomaly detection algorithms such as Gaussian, binary association rule and fuzzy association rule by using sensor data from various domains such as rainfall, temperature and cancer cell data. Receiver operating characteristic curves are used for comparing the performance of our proposed BRBAR with the aforementioned algorithms. The comparisons demonstrate that BRBAR is more accurate and reliable in detecting anomalies from sensor data under uncertainty. Hence, the use of such algorithm to feed the decision-making systems could be beneficial. Therefore, we have used this algorithm to feed appropriate sensor data to our recently developed belief-rule-based expert system to predict flooding in an area. Consequently, the reliability and the accuracy of the flood prediction system increase significantly. Such novel algorithm (BRBAR) can be used in other areas of applications. 

  • 15.
    Alam, Md. Eftekhar
    et al.
    International Islamic University Chittagong, Bangladesh.
    Kaiser, M. Shamim
    Jahangirnagar University, Dhaka, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    An IoT-Belief Rule Base Smart System to Assess Autism2018In: Proceedings of the 4th International Conference on Electrical Engineering and Information & Communication Technology (iCEEiCT 2018), IEEE, 2018, p. 671-675Conference paper (Refereed)
    Abstract [en]

    An Internet-of-Things (IoT)-Belief Rule Base (BRB) based hybrid system is introduced to assess Autism spectrum disorder (ASD). This smart system can automatically collect sign and symptom data of various autistic children in realtime and classify the autistic children. The BRB subsystem incorporates knowledge representation parameters such as rule weight, attribute weight and degree of belief. The IoT-BRB system classifies the children having autism based on the sign and symptom collected by the pervasive sensing nodes. The classification results obtained from the proposed IoT-BRB smart system is compared with fuzzy and expert based system. The proposed system outperformed the state-of-the-art fuzzy system and expert system.

  • 16.
    alam, M.E.
    et al.
    Electrical Electronic Engineering, International Islamic University, Chittagong, Bangladesh.
    Kaiser, M. Shamim
    Institute of Information Technology, Jahangirnagar University, Dhaka, Bangladesh.
    Hossain, M.S.
    Computer Science Engineering, University of Chittagong, Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    An IoT-belief rule base smart system to assess autism2018Conference paper (Refereed)
    Abstract [en]

    An Internet-of-Things (IoT)-Belief Rule Base (BRB) based hybrid system is introduced to assess Autism spectrum disorder (ASD). This smart system can automatically collect sign and symptom data of various autistic children in real-time and classify the autistic children. The BRB subsystem incorporates knowledge representation parameters such as rule weight, attribute weight and degree of belief. The IoT-BRB system classifies the children having autism based on the sign and symptom collected by the pervasive sensing nodes. The classification results obtained from the proposed IoT-BRB smart system is compared with fuzzy and expert based system. The proposed system outperformed the state-of-the-art fuzzy system and expert system.

  • 17.
    Monrat, Ahmed Afif
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Challenges and Opportunities of Using Big Data for Assessing Flood Risks2018In: Applications of Big Data Analytics: Trends, Issues, and Challenges / [ed] Mohammed M. Alani, Hissam Tawfik, Mohammed Saeed, Obinna Anya, Cham: Springer, 2018, p. 31-42Chapter in book (Refereed)
    Abstract [en]

    Among the various natural calamities, flood is considered one of the most catastrophic natural hazards, which has disastrous impact on the socioeconomic lifeline of a country. Nowadays, business organizations are using Big Data to improve their strategies and operations for revealing patterns and market trends to increase revenues. Eventually, the crisis response teams of a country have turned their interest to explore the potentialities of Big Data in managing disaster risks such as flooding. The reason for this is that during flooding, crisis response teams need to take decisions based on the huge amount of incomplete and inaccurate information, which are mainly coming from three major sources, including people, machines, and organizations. Hence, Big Data technologies can be used to monitor and to determine the people exposed to the risks of flooding in real time. This could be achieved by analyzing and processing sensor data streams coming from various sources as well as data collected from other sources such as Twitter, Facebook, and satellite and also from disaster organizations of a country by using Big Data technologies. Therefore, this chapter explores the challenges, the opportunities, and the methods, required to leverage the potentiality of Big Data to assess and predict the risk of flooding.

  • 18.
    Siddiquee, Kazy Noor E Alam
    et al.
    University of Science and Technology, Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Moreno Arrebola, Francisco Javier
    HeidelbergCement, Spain.
    Abedin, Md. Zainal
    University of Science and Technology, Chittagong, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Estimation of Signal Coverage and Localization in Wi-Fi Networkswith AODV and OLSR2018In: Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, ISSN 2093-5374, E-ISSN 2093-5382, Vol. 9, no 3, p. 11-24, article id 2Article in journal (Refereed)
    Abstract [en]

    For estimation of signal coverage and localization, path loss is the major component for link budget of any communication system. Instead of traditional Doppler shift or Doppler spread techniques, the path loss has been chosen for IEEE 802.11 (Wi-Fi) signals of 2.5 and 5 GHz to measure the signal coverage and localization in this research. A Wi-Fi system was deployed in a MANET (Mobile Adhoc NETwork), involving both mobile and stationary nodes. The Adhoc network was also assessed in a routing environment under AODV and OLSR protocols. The proposal was evaluated using the OPNET Modeler simulation environment.

  • 19.
    Cherkaoui, S
    et al.
    Université de Sherbrooke, Canada.
    Andersson, KarlLuleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    LCN 2018 Message from the Program Chairs2018Conference proceedings (editor) (Refereed)
  • 20.
    Abedin, Md. Zainal
    et al.
    University of Science and Technology, Chittagong.
    Siddiquee, Kazy Noor E Alam
    University of Science and Technology Chittagong.
    Bhuyan, M. S.
    University of Science & Technology Chittagong.
    Karim, Razuan
    University of Science and Technology Chittagong.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Performance Analysis of Anomaly Based Network Intrusion Detection Systems2018In: Proveedings of the 43nd IEEE Conference on Local Computer Networks Workshops (LCN Workshops), Piscataway, NJ: IEEE Computer Society, 2018, p. 1-7Conference paper (Refereed)
    Abstract [en]

    Because of the increased popularity and fast expansion of the Internet as well as Internet of things, networks are growing rapidly in every corner of the society. As a result, huge amount of data is travelling across the computer networks that lead to the vulnerability of data integrity, confidentiality and reliability. So, network security is a burning issue to keep the integrity of systems and data. The traditional security guards such as firewalls with access control lists are not anymore enough to secure systems. To address the drawbacks of traditional Intrusion Detection Systems (IDSs), artificial intelligence and machine learning based models open up new opportunity to classify abnormal traffic as anomaly with a self-learning capability. Many supervised learning models have been adopted to detect anomaly from networks traffic. In quest to select a good learning model in terms of precision, recall, area under receiver operating curve, accuracy, F-score and model built time, this paper illustrates the performance comparison between Naïve Bayes, Multilayer Perceptron, J48, Naïve Bayes Tree, and Random Forest classification models. These models are trained and tested on three subsets of features derived from the original benchmark network intrusion detection dataset, NSL-KDD. The three subsets are derived by applying different attributes evaluator’s algorithms. The simulation is carried out by using the WEKA data mining tool.

  • 21.
    Zhohov, Roman
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Minovski, Dimitar
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. InfoVista Sweden.
    Johansson, Per
    InfoVista Sweden.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Real-time Performance Evaluation of LTE for IIoT2018In: Proceedings of the 43rd IEEE Conference on Local Computer Networks (LCN) / [ed] Soumaya Cherkaoui, Institute of Electrical and Electronics Engineers (IEEE), 2018Conference paper (Refereed)
    Abstract [en]

    Industrial Internet of Things (IIoT) is claimed to be a global booster technology for economic development. IIoT brings bulky use-cases with a simple goal of enabling automation, autonomation or just plain digitalization of industrial processes. The abundance of interconnected IoT and CPS generate additional burden on the telecommunication networks, imposing number of challenges to satisfy the key performance requirements. In particular, the QoS metrics related to real-time data exchange for critical machine-to-machine type communication. This paper analyzes a real-world example of IIoT from a QoS perspective, such as remotely operated underground mining vehicle. As part of the performance evaluation, a software tool is developed for estimating the absolute, one-way delay in end-toend transmissions. The measured metric is passed to a machine learning model for one-way delay prediction based on LTE RAN measurements using a commercially available cutting-edge software tool. The achieved results prove the possibility to predict the delay figures using machine learning model with a coefficient of determination up to 90%.

  • 22.
    Andersson, Karl
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    You, Ilsun
    Soonchunhyang University, Chungcheongnam-do, Republic of Korea.
    Palmieri, Francesco
    University of Salerno, Fisciano (SA), Italy.
    Security and Privacy for Smart, Connected, and Mobile IoT Devices and Platforms2018In: Security and Communication Networks, ISSN 1939-0114, E-ISSN 1939-0122, Vol. 2018, p. 1-2, article id 5346596Article in journal (Refereed)
  • 23.
    Hossain, Mohammad Shahadat
    et al.
    University of Chittagong, Bangladesh.
    Rahaman, Saifur
    Department of Computer Science and Engineering, International Islamic University Chittagong.
    Kor, Ah-Lian
    School of Computing, Creative Technologies and Engineering, Leeds Beckett University.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Pattison, Colin
    School of Computing, Creative Technologies and Engineering, Leeds Beckett University.
    A Belief Rule Based Expert System for Datacenter PUE Prediction under Uncertainty2017In: IEEE Transactions on Sustainable Computing, ISSN 2377-3782, Vol. 2, no 2, p. 140-153Article in journal (Refereed)
    Abstract [en]

    A rapidly emerging trend in the IT landscape is the uptake of large-scale datacenters moving storage and data processing to providers located far away from the end-users or locally deployed servers. For these large-scale datacenters, power efficiency is a key metric, with the PUE (Power Usage Effectiveness) and DCiE (Data Centre infrastructure Efficiency) being important examples. This article proposes a belief rule based expert system to predict datacenter PUE under uncertainty. The system has been evaluated using real-world data from a data center in the UK. The results would help planning construction of new datacenters and the redesign of existing datacenters making them more power efficient leading to a more sustainable computing environment. In addition, an optimal learning model for the BRBES demonstrated which has been compared with ANN and Genetic Algorithm; and the results are promising.

  • 24.
    Hossain, Mohammad Shahadat
    et al.
    University of Chittagong, Bangladesh.
    Ahmed, Faisal
    University of Chittagong, Bangladesh.
    Tuj-Johora, Fatema
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Belief Rule Based Expert System to Assess Tuberculosis under Uncertainty2017In: Journal of medical systems, ISSN 0148-5598, E-ISSN 1573-689X, Vol. 41, no 3, article id 43Article in journal (Refereed)
    Abstract [en]

    The primary diagnosis of Tuberculosis (TB) is usually carried out by looking at the various signs and symptoms of a patient. However, these signs and symptoms cannot be measured with 100\% certainty since they are associated with various types of uncertainties such as vagueness, imprecision, randomness, ignorance and incompleteness. Consequently, traditional primary diagnosis, based on these signs and symptoms, which is carried out by the physicians, cannot deliver reliable results. Therefore, this article presents the design, development and applications of a Belief Rule Based Expert System (BRBES) with the ability to handle various types of uncertainties to diagnose TB. The knowledge base of this system is constructed by taking experts' suggestions and by analyzing historical data of TB patients. The experiments, carried out, by taking the data of 100 patients demonstrate that the BRBES's generated results are more reliable than that of human expert as well as fuzzy rule based expert system. 

  • 25.
    Hossain, Mohammad Shahadat
    et al.
    University of Chittagong, Bangladesh.
    Habib, Israt Binteh
    University of Chittagong.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Belief Rule based Expert System to Diagnose Dengue Fever under Uncertainty2017In: Proceedings of Computing Conference 2017 / [ed] Liming Chen, Nikola Serbedzija, Kami Makki, Nazih Khaddaj Mallat, Kohei Arai, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 179-186Conference paper (Refereed)
    Abstract [en]

    Dengue Fever is a debilitating mosquito-borne disease, causing sudden fever, leading to fatality in many cases. A Dengue patient is diagnosed by the physicians by looking at the various signs, symptoms and risk factors of this disease. However, these signs, symptoms and the risk factors cannot be measured with 100% certainty since various types of uncertainties such as imprecision, vagueness, ambiguity, and ignorance are associated with them. Hence, it is difficult for the physicians to diagnose the dengue patient accurately since they don’t consider the uncertainties as mentioned. Therefore, this paper presents the design, development and applications of an expert system by incorporating belief rule base as the knowledge representation schema as well as the evidential reasoning as the inference mechanism with the capability of handling various types of uncertainties to diagnose dengue fever. The results generated from the expert system are more reliable than from fuzzy rule based system or from human expert.

  • 26.
    Siddiquee, Kazy Noor E Alam
    et al.
    University of Science and Technology Chittagong.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Khan, Faria Farjana
    University of Science and Technology Chittagong, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    A Scalable and Secure MANET for an i-Voting System2017In: Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, ISSN 2093-5374, E-ISSN 2093-5382, Vol. 8, no 3, p. 1-17, article id 1Article in journal (Refereed)
    Abstract [en]

    Internet Voting (i-Voting) is an online electronic voting process where a voter can vote staying online from anywhere or connected to a wireless network of a target place. In this paper, a wireless network built with a MANET has been considered for the voting process. National parliamentary voting process of Bangladesh has been taken as the case study. The MANET of the voting process is built using some stationary wireless nodes and mobile wireless nodes. Voters carry mobile wireless nodes using which they can vote. Stationary wireless nodes are installed and deployed in the MANET built in a polling area selected by the National Agency of Election process. These nodes are directly in connection with the national database of voters. Stationary nodes perform the authentication and validation processes of the voter (a mobile node) before the vote is given and casted. The secured transaction of data is the goal to be occurred and routed after a strong authentication and validation of the user has been confirmed. The whole process is completed in a scalable wireless network with a distributed goal based approach. Total processes are followed by secured routing of data in this MANET. The optimal routing protocol among OLSR, AODV, DSR, TORA and GRP has been chosen. Denial of Service (DoS) attacks have been considered as the major threat on nodes in this MANET. The simulation work is done in the OPNET simulator.

  • 27.
    Hridoy, Md Rafiul Sabbir
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    Department of Computer Science and Engineering, University of Chittagong.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Web Based Belief Rule Based Expert System for Assessing Flood Risk2017In: iiWAS'17: Proceedings of the 19th International Conference on Information Integration and Web-based Applications & Services, New York: ACM Digital Library, 2017, p. 434-440Conference paper (Refereed)
    Abstract [en]

    Natural calamities such as flooding, volcanic eruption, tornado hampers our daily life and causes many sufferings. Flood is one of the most catastrophic among the natural calamities. Assessing flood risk helps us to take necessary steps and save human lives. Several heterogeneous factors are used to assess flood risk on the livelihood of an area. Moreover, several types of uncertainties can be associated with each factor. In this paper, we propose a web based flood risk assessment expert system by combining belief rule base with the capability of reading data and generating web-based output. This paper also introduces a generic RESTful API which can be used without writing the belief rule based expert system from scratch. This expert system will facilitate the monitoring of the various flood risk factors, contributing in increasing the flood risk on livelihood of an area. Eventually, the decision makers should be able to take measures to control those factors and to reduce the risk of flooding in an area. Data for the expert system has been collected from a case study area by conducting interviews.

  • 28.
    Abedin, Md. Zainal
    et al.
    University of Science and Technology Chittagong.
    Chowdhury, Abu Sayeed
    University of Science and Technology Chittagong.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Karim, Razuan
    University of Science and Technology Chittagong.
    An Interoperable IP based WSN for Smart Irrigation Systems2017Conference paper (Refereed)
    Abstract [en]

    Wireless Sensor Networks (WSN) have been highly developed which can be used in agriculture to enable optimal irrigation scheduling. Since there is an absence of widely used available methods to support effective agriculture practice in different weather conditions, WSN technology can be used to optimise irrigation in the crop fields. This paper presents architecture of an irrigation system by incorporating interoperable IP based WSN, which uses the protocol stacks and standard of the Internet of Things paradigm. The performance of fundamental issues of this network is emulated in Tmote Sky for 6LoWPAN over IEEE 802.15.4 radio link using the Contiki OS and the Cooja simulator. The simulated results of the performance of the WSN architecture presents the Round Trip Time (RTT) as well as the packet loss of different packet size. In addition, the average power consumption and the radio duty cycle of the sensors are studied. This will facilitate the deployment of a scalable and interoperable multi hop WSN, positioning of border router and to manage power consumption of the sensors.

  • 29.
    Booth, Todd
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Critical Infrastructure Network DDoS Defense, via Cognitive Learning2017In: / [ed] Pietro Manzoni, Universitat Politècnica de València, Spain, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017Conference paper (Refereed)
    Abstract [en]

    Some public and private services are called part of the Critical Infrastructure (CI), which are considered as the most important services to protect the functioning of a society and the economy.  Many CIs provide services via the Internet and thus cyber-attacks can be performed remotely.  It is now very simple and free to find and download software, which automates performing cyber-attacks.  A recent example is that two teenagers, with close to no security knowledge, created an on-line business. They would run cyber-attacks (online booter service called vDOS, as reported by Brian Krebs) for a small fee. They reportedly earned over 600,000 USD in a short period of time by conducting a large number of automated DDoS cyber-attacks. Then Krebs was retaliated against, and the highest DDoS attack bandwidth ever recorded, 620 Gbps, was launched against Krebs. In this paper we show how cognitive learning can be used to significantly mitigate any effects of DDoS network attacks, against the critical infrastructure.

  • 30.
    Booth, Todd
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    DNS DDoS Mitigation, via DNS Timer Design Changes2017In: Future Network Systems and Security: Third International Conference, FNSS 2017, Gainesville, FL, USA, August 31 - September 2, 2017, Proceedings / [ed] Robin Doss, Welwyn Piramuthu, Wei Zhou, Springer, 2017, p. 43-55Conference paper (Refereed)
    Abstract [en]

    DDoS attacks have been a problem since 2000. In October 2016, there was a major DDoS attack against the service provider Dyn’s DNS service, which took the service down. This was one of the largest bandwidth DDoS attack ever documented, with attack bandwidth over 650 Gbps. By taking down just Dyn’s DNS service, clients could not obtain the IP addresses, of the organizations hosting their DNS with Dyn, such as Twitter. Our contribution is that we have found a way to mitigate the effect of DDoS attacks against DNS services. We only require some very small algorithm changes, in the DNS protocol. More specifically, we propose to add two additional timers. Even if the end DNS clients don’t support these timers, they will receive our new functionality via the DNS resolvers and recursive servers. In summary, our contributions give much more control to the organizations, as to under which specific conditions the DNS cache entries should be aged or used. This allows the organization to (1) much more quickly expire client DNS caches and (2) to mitigate the DDoS DNS attack effects. Our contributions are also helpful to organizations, even if there are no DDoS DNS attack.

  • 31.
    Ul Islam, Raihan
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Heterogeneous Wireless Sensor Networks Using CoAP and SMS to Predict Natural Disasters2017In: Proceedings of the 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS): The 8th IEEE INFOCOM International Workshop on Mobility Management in the Networks of the Future World (MobiWorld'17),, Piscataway, NJ: IEEE Communications Society, 2017, p. 30-35Conference paper (Refereed)
    Abstract [en]

    Even in the 21 st century human is still handicapped with natural disaster. Flood is one of the most catastrophic natural disasters. Early warnings help people to take necessary steps to save human lives and properties. Sensors can be used to provide more accurate early warnings due to possibilities of capturing more detail data of surrounding nature. Recent advantages in protocol standardization and cost effectiveness of sensors it is possible to easily deploy and manage sensors in large scale. In this paper, a heterogeneous wireless sensor network is proposed and evaluated to predict natural disaster like flood. In this network CoAP is used as a unified application layer protocol for exchanging sensor data. Therefore, CoAP over SMS protocol is used for exchanging sensor data. Furthermore, the effectiveness of the heterogeneous wireless sensor network for predicting natural disaster is presented in this paper.

  • 32.
    Rondeau, Éric
    et al.
    University of Lorraine.
    Khouki, Lyes
    University of Technology of Troyes.
    Georges, Jean-Philippe
    University of Lorraine.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Cherkaoui, Soumaya
    Sherbrooke University.
    On-Move 2016: Message from the Chairs2017In: Proceedings - Conference on Local Computer Networks, LCN, Piscataway, NJ, 2017, Vol. F126504, p. xxiv-, article id 7856126Conference paper (Refereed)
  • 33.
    Cherkaoui, Soumaya
    et al.
    Sherbrooke University.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Khoukhi, Lyes
    University of Technology of Troyes.
    Sahoo, Jagruti
    South Carolina State University.
    Johansson, Dan
    Umeå universitet.
    On-Move 2017 Message from the Chairs2017In: Proceedings: 2017 IEEE 42nd Conference on Local Computer Networks Workshops, LCN Workshops 2017, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. xv-, article id 8110191Conference paper (Refereed)
  • 34.
    Siddiquee, Kazy Noor E Alam
    et al.
    University of Science and Technology Chittagong.
    Khan, Faria Farjana
    University of Science and Technology Chittagong.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Optimal Dynamic Routing Protocols for Agro-Sensor Communication in MANETs2017Conference paper (Refereed)
    Abstract [en]

    Recent developments in the area of Wireless sensor networks and Mobile ad hoc networks provide flexible and easy- to-deploycommunication means for a wide range of appli- cations without any need for an infrastructure being pre-con- figured. Our paper studies performance of proactive and reactive routing protocols in a scenario with agro-sensors. Our results, achieved by simulating a network both in OPNET Modeler and NS2, show that the AODV routing protocol performs better for a large-scale network (where node density is higher) while the DSR routing protocol performs better in a small-scale network given the particular scenario we studied.

  • 35.
    Siddiquee, Kazy Noor E. Alam
    et al.
    University of Science & Technology Chittagong, Department of Computer Science & Engineering, Foys Lake, Chittagong.
    Sarma, Dhiman
    Rangamati Science & Technology University, Department of Computer Science & Engineering, Rangamati.
    Nandi, Avijit
    University of Science & Technology Chittagong, Department of Computer Science & Engineering, Foys Lake, Chittagong.
    Akhter, Sharmin
    University of Science & Technology Chittagong, Department of Computer Science & Engineering, Foys Lake, Chittagong.
    Hossain, Sohrab
    University of Science & Technology Chittagong, Department of Computer Science & Engineering, Foys Lake, Chittagong.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    University of Chittagong, Department of Computer Science & Engineering, Chittagong.
    Performance Analysis of a Surveillance System to Detect and Track Vehicles using Haar Cascaded Classifiers and Optical Flow method2017In: Proceedings of the 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), New York: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 258-263Conference paper (Refereed)
    Abstract [en]

    This paper presents the real time vehicle detection and tracking system, based on data, collected from a single camera. In this system, vehicles are detected by using Haar Feature-based Cascaded Classifier on static images, extracted from the video file. The advantage of this classifier is that, it uses floating numbers in computations and hence, 20% more accuracy can be achieved in comparison to other classifiers and features of classifiers such as LBP (Local Binary Pattern). Tracking of the vehicles is carried out using Lucas-Kanade and Horn Schunk Optical Flow method because it performs better than other methods such as Morphological and Correlation Transformations. The proposed system consists of vehicle detection and tracking; and it is evaluated by using real data, collected from the route networks of Chittagong City of Bangladesh.

  • 36.
    Siddiquee, Kazy Noor E Alam
    et al.
    University of Science and Technology Chittagong.
    Dhiman, Sarma
    Department of Computer Science and Engineering, Rangamati Science and Technology University, Rangamati.
    Nandi, Avijit
    Department of Computer Science and Engineering, University of Science and Technology Chittagong Foy's Lake, Chittagong, Bangladesh.
    Akhter, Sharmin
    Department of Computer Science and Engineering, University of Science and Technology Chittagong Foy's Lake, Chittagong, Bangladesh.
    Hossain, Sohrab
    Department of Computer Science and Engineering, University of Science and Technology Chittagong, Foy's Lake, Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Performance analysis of a surveillance system to detect and track vehicles using Haar cascaded classifiers and optical flow method2017In: 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 258-263, article id 17595122Conference paper (Refereed)
    Abstract [en]

    This paper presents the real time vehicle detection and tracking system, based on data, collected from a single camera. In this system, vehicles are detected by using Haar Feature-based Cascaded Classifier on static images, extracted from the video file. The advantage of this classifier is that, it uses floating numbers in computations and hence, 20% more accuracy can be achieved in comparison to other classifiers and features of classifiers such as LBP (Local Binary Pattern). Tracking of the vehicles is carried out using Lucas-Kanade and Horn Schunk Optical Flow method because it performs better than other methods such as Morphological and Correlation Transformations. The proposed system consists of vehicle detection and tracking; and it is evaluated by using real data, collected from the route networks of Chittagong City of Bangladesh.

  • 37.
    Hedemalm, Emil
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hallberg, Josef
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Kor, Ah-Lian
    Leeds Beckett University.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Pattinson, Colin
    School of Computing, Creative Technologies & Engineering, Leeds Beckett University.
    Promoting green transportation via persuasive games2017In: International SEEDS Conference 2017: Sustainable Ecological Engineering Design for Society – 13th & 14th September 2017, 2017Conference paper (Refereed)
    Abstract [en]

    It is now widely accepted that human behaviour accounts for a large portion of total global emissions, and thus influences climate change to a large extent (IPCC, 2014). Changing human behaviour when it comes to mode of transportation is one component which could make a difference in the long term. In order to achieve behavioural change, we investigate the use of a persuasive multiplayer game. Transportation mode recognition is used within the game to provide bonuses and penalties to users based on their daily choices regarding transportation. Preliminary results from testers of the game indicate that using games may be successful in causing positive change in user behaviour.

  • 38.
    Abedin, Md. Zainal
    et al.
    University of Science and Technology, Chittagong.
    Paul, Sukanta
    University of Science and Technology, Chittagong.
    Akhter, Sharmin
    University of Science and Technology, Chittagong.
    Siddiquee, Kazy Noor E Alam
    University of Science and Technology, Chittagong.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Selection of Energy Efficient Routing Protocol for Irrigation Enabled by Wireless Sensor Networks2017In: Proceedings of 2017 IEEE 42nd Conference on Local Computer Networks Workshops, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 75-81Conference paper (Refereed)
    Abstract [en]

    Wireless Sensor Networks (WSNs) are playing remarkable contribution in real time decision making by actuating the surroundings of environment. As a consequence, the contemporary agriculture is now using WSNs technology for better crop production, such as irrigation scheduling based on moisture level data sensed by the sensors. Since WSNs are deployed in constraints environments, the life time of sensors is very crucial for normal operation of the networks. In this regard routing protocol is a prime factor for the prolonged life time of sensors. This research focuses the performances analysis of some clustering based routing protocols to select the best routing protocol. Four algorithms are considered, namely Low Energy Adaptive Clustering Hierarchy (LEACH), Threshold Sensitive Energy Efficient sensor Network (TEEN), Stable Election Protocol (SEP) and Energy Aware Multi Hop Multi Path (EAMMH). The simulation is carried out in Matlab framework by using the mathematical models of those algortihms in heterogeneous environment. The performance metrics which are considered are stability period, network lifetime, number of dead nodes per round, number of cluster heads (CH) per round, throughput and average residual energy of node. The experimental results illustrate that TEEN provides greater stable region and lifetime than the others while SEP ensures more througput.

  • 39.
    Booth, Todd
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Centre for Critical Infrastructure and Societal Security.
    Stronger Authentication for Password Credential Internet Services2017In: Proceedings of the 2017 Third Conference on Mobile and Secure Services (MOBISECSERV) / [ed] Pascal Urien, Selwyn Piramuthu, Piscataway, NJ: IEEE conference proceedings, 2017, p. 41-45, article id 7886566Conference paper (Refereed)
    Abstract [en]

    Most Web and other on-line service providers (”Inter- net Services”) only support legacy ID (or email) and password (ID/PW) credential authentication. However, there are numerous vulnerabilities concerning ID/PW credentials. Scholars and the industry have proposed several improved security solutions, such as MFA, however most of the Internet Services have refused to adopt these solutions. Mobile phones are much more sensitive to these vulnerabilities (so this paper focuses on mobile phones). Many users take advantage of password managers, to keep track of all their Internet Service profiles. However, the Internet Service profiles found in password managers, are normally kept on the PC or mobile phone’s disk, in an encrypted form. Our first contribution is a design guideline, whereby the Internet Service profiles never need to touch the client’s disk. Most users would benefit, if they had the ability to use MFA, to login to a legacy Internet Service, which only supports ID/PW credential authentication. Our second contribution is a design guideline, whereby users can choose, for each legacy ID/PW Internet Service, which specific MFA they wish to use. We have also presenting conceptual design guidelines, showing that both of our contributions are minor changes to existing password managers, which can be implemented easily with low overhead.

  • 40.
    Andersson, Karl
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Rondeau, Éric
    University of Lorraine.
    Kor, Ah-Lian
    School of Computing, Creative Technologies and Engineering, Leeds Beckett University.
    Johansson, Dan
    Umea University, Department of Informatics.
    Sustainable Mobile Computing and Communications2017In: Mobile Information Systems, ISSN 1574-017X, Vol. 2017, article id 1098264Article in journal (Refereed)
  • 41.
    Karim, Razuan
    et al.
    Department of Computer Science and Engineering , University of Science and Technology Chittagong.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Hossain, Mohammad Shahadat
    Department of Computer Science and Engineering , University of Chittagong.
    Uddin, Md. Jasim
    Department of Computer Science and Engineering , University of Science and Technology Chittagong.
    Meah, Md. Perveg
    Department of Computer Science and Engineering , University of Science and Technology Chittagong.
    A Belief Rule Based Expert System to Assess Clinical Bronchopneumonia Suspicion2016In: Proceedings of Future Technologies Conference 2016 (FTC 2016) / [ed] Flavio Villanustre and Arjuna Chala, IEEE, 2016, p. 655-660Conference paper (Refereed)
    Abstract [en]

    Bronchopneumonia is an acute or chronic inflammation of the lungs, in which the alveoli and/or interstitial are affected. Usually the diagnosis of Bronchopneumonia is carried out using signs and symptoms of this disease, which cannot be measured since they consist of various types of uncertainty. Consequently, traditional disease diagnosis, which is performed by a physician, cannot deliver accurate results. Therefore, this paper presents the design, development and application of an expert system for assessing the suspicion of Bronchopneumonia under uncertainty. The Belief Rule-Based Inference Methodology using the Evidential Reasoning (RIMER) approach was adopted to develop this expert system, which is named the Belief Rule-Based Expert System (BRBES). The system can handle various types of uncertainty in knowledge representation and inference procedures. The knowledge base of this system was constructed by using real patient data and expert opinion. Practical case studies were used to validate the system. The system-generated results are more effective and reliable in terms of accuracy than from the results generated by a manual system.

  • 42.
    Klimova, Alexandra
    et al.
    ITMO University.
    Rondeau, Eric
    Université de Lorraine, Nancy.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Porras, Jari
    Lappeenranta University of Technology.
    Rybin, Andrei
    ITMO University.
    Zaslavsky, Arkady
    CSIRO, Australia.
    An international Master’s program in green ICT as a contribution to sustainable development2016In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 135, p. 223-239Article in journal (Refereed)
    Abstract [en]

    Various principles of sustainable development are currently being integrated into national policies and programs. Such principles relate to a range of aspects of human activities requiring urgent attention, including heating, mobility, food security, and sustainable agriculture. One of the fields contributing to the transition towards a sustainable society is that of green information and communication technologies (ICT). Therefore, the implementation of educational programs in green ICT is important in ensuring further ICT development around sustainability concerns. This article describes the development of an international Master's degree program named “Pervasive computing and communications for sustainable development” (PERCCOM) by an international consortium, which aimed to combine advanced ICT with environmental, economic, and social awareness. The article presents background information regarding the role of the ICT sector in environmental challenges, and a review of the literature, in order to understand what is required of ICT and green ICT graduates. The curriculum of the PERCCOM program is then described and findings on program improvement are reported. The article is aimed at academic and research professionals in the fields of sustainable development and green technologies, with the goal of improving educational initiatives to address the societal demand for sustainable development. The findings reported here contribute toward the search for a solution for sustainability, especially regarding environmental issues, among educating professionals with high expertise in networking, computing, and programming, who are able to design, develop, deploy, and maintain both pervasive computing systems and communication architectures for sustainable development.

  • 43.
    Thombre, Sumeet
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    IP based Wireless Sensor Networks: performance Analysis using Simulations and Experiments2016In: Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, ISSN 2093-5374, E-ISSN 2093-5382, Vol. 7, no 3, p. 53-76Article in journal (Refereed)
    Abstract [en]

    Wireless sensor networks are at the crux of the Internet of Things applications. At the current state, there exist several technologies competing against each other in the IoT space. These proprietary technologies and hardware pose a serious problem of interoperability, which is vital to unleash the vision of the Internet of Things. Moreover, the traditional approach towards wireless sensor networks was to be unlike the internet, primarily because of the power and memory constraints posed by the tiny sensor nodes. The IETF 6LoWPAN technology facilitates the usage of IPv6 communications in sensor networks, which helps solve the problem of interoperability, enabling low power, low cost micro-controllers to be globally connected to the internet. Another IETF technology, CoAP allows interactive communication over the internet for these resource constrained devices. Along with 802.15.4, 6LoWPAN and CoAP, an open, standardized WSN stack for resource constrained devices and environments becomes available. The Contiki OS, touted as the open source OS for IoT, provides low power IPv6 communications and supports the 6LoWPAN and CoAP protocols, along with mesh routing using RPL. Along with these, a CoAP framework, Californium (Cf) provides a scalable and RESTful API to handle IoT devices. These open tools and technologies are employed in this work to form an open, inter-operable, scalable, reliable and low power WSN stack. This stack is then simulated using Contiki's default network simulator Cooja, to conduct performance analysis in varying conditions such as noise, topology, traffic etc. Finally, as a proof of concept and a validation of the simulated stack, physical deployment is carried out, using a Raspberry Pi as a border router, which connects the wireless sensor network to the global internet along with the T-mote sky sensor motes. Therefore, this work develops and demonstrates an open, interoperable, reliable, scalable, low power, low cost WSN stack, both in terms of simulations and physical deployments, and carries out performance evaluation of the stack in terms of throughput, latency and packet loss.

  • 44.
    Booth, Todd
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Network DDoS Layer 3/4/7 Mitigation via Dynamic Web Redirection2016In: Future Network Systems and Security: Second International Conference, FNSS 2016, Paris, France, November 23-25, 2016, Proceedings / [ed] Robin Doss, Selwyn Piramuthu, Wei Zhou, New York: Springer, 2016, p. 111-125Conference paper (Refereed)
    Abstract [en]

    Layer 3, 4 and 7 DDoS attacks are common and very difficult to defend against. The academic community has published hundreds of well thought out algorithms, which require changes in computer networking equipment, to better detect and mitigate these attacks. The problem with these solutions, is that they require computer networking manufacturers to make changes to their hardware and/or software. On the other hand, with our solution, absolutely no hardware or software changes are required. We only require the use of BGP4 Flow-Spec, which has already been widely deployed many years ago. Further the customers’ own ISP does not require Flow-Spec. Our algorithm protects groups of over sixty-five thousand different customers, via the aggregation into one very small Flow-Spec rule. In this paper, we propose our novel, low cost and efficient solution, to both detect and greatly mitigate any and all types of L347 DDoS Web attacks.

  • 45.
    Porras, Jari
    et al.
    Lappeenranta University of Technology.
    Seffah, Ahmed
    Lappeenranta University of Technology.
    Rondeau, Eric
    Université de Lorraine, Nancy.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Klimova, Alexandra
    ITMO University.
    PERCCOM: A Master Program in Pervasive Computing and COMmunications for Sustainable Development2016In: 2016 IEEE 29th International Conference on Software Engineering Education and Training (CSEET): Dallas, TX, 5-6 April 2016, Piscataway, NJ: IEEE Communications Society, 2016, p. 204-212, article id 7474485Conference paper (Refereed)
    Abstract [en]

    This paper presents the Erasmus Mundus Joint Master Degree in Pervasive Computing and Communications for Sustainable Development (PERCCOM). This program brings together 11 academic partners and 8 industry partners to combine advanced Information and Communication Technologies (ICT) with environmental awareness to enable world-class education and unique competences for ICT professionals who can build cleaner, greener, more resource and energy efficient cyber-physical systems. First, this paper describes the rationale and motivations for ICT education for sustainability challenges. It then details the structure and contents of the programs including the courses offered at the three teaching locations (Nancy France, Lappeenranta Finland, and Lulea Sweden). The ways that the program has been running as well as students selection, their thesis works, involvement of industry, are also discussed. The program was built and managed using a solid academic standards and strategies student-centered learning.

  • 46.
    Thombre, Sumeet
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Hossain, Mohammad Shahadat
    University of Chittagong.
    Performance Analysis of an IP based Protocol Stack for WSNs2016In: Proceedings of the 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Piscataway, NJ: IEEE Communications Society, 2016, p. 691-696, article id 7562102Conference paper (Refereed)
    Abstract [en]

    Wireless sensor networks (WSNs) are the key enablers of the internet of things (IoT) paradigm. Traditionally, sensor network research has been to be unlike the internet, motivated by power and device constraints. The IETF 6LoWPAN draft standard changes this, defining how IPv6 packets can be efficiently transmitted over IEEE 802.15.4 radio links. Due to this 6LoWPAN technology, low power, low cost micro-controllers can be connected to the internet forming what is known as the wireless embedded internet. Another IETF recommendation, CoAP allows these devices to communicate interactively over the internet. The integration of such tiny, ubiquitous electronic devices to the internet enables interesting real-time applications. We evaluate the performance of a stack consisting of CoAP and 6LoWPAN over the IEEE 802.15.4 radio link using the Contiki OS and Cooja simulator, along with the CoAP framework Californium (Cf).

  • 47.
    Hossain, Mohammad Shahadat
    et al.
    University of Chittagong.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Naznin, Samina
    Department of Computer Science and Engineering, University of Chittagong.
    A Belief Rule Based Expert System to Diagnose Measles under Uncertainty2015In: Proceedings of the 2015 International Conference on Health Informatics and Medical Systems (HIMS'15) / [ed] Hamid R. Arabnia; Leonidas Deligiannidis; George Jandieri; Ashu M. G. Solo; Fernando G. Tinetti, CSREA Press, 2015, p. 17-23Conference paper (Refereed)
    Abstract [en]

    Measles is a highly infectious child disease that causes serious complications and death worldwide. Measles is generally diagnosed from its signs and symptoms by a physician, which cannot be measured with 100% certainty during the diagnosis process. Consequently, the traditional way of diagnosing measles from its signs and symptoms lacks the accuracy. Therefore, a belief rule-based inference methodology using evidential reasoning approach (RIMER), which is capable of handling various types of uncertainties has been used to develop an expert system to diagnose measles under uncertainty. The results, generated, from the system have been compared with the expert opinion as well as with a Fuzzy Logic based system. In both the cases, it has been found that the Belief Rule Based Expert (BRBES), presented in this paper, is more reliable and accurate.

  • 48.
    Andersson, Karl
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Hossain, Mohammad Shahadat
    University of Chittagong.
    Thapa, Devinder
    Department of Information Systems, University of Agder.
    Zander, Pär-Ola
    Department of Communication and Psychology, Aalborg University.
    A Novel Framework of an Expert System by integrating Capability Approach and BRB to Evaluate E-Government Services2015In: Proceedings of eChallenges e-2015 Conference / [ed] Paul Cunningham; Miriam Cunningham, IIMC International Information Management Corporation Ltd , 2015, p. 1-12, article id 68Conference paper (Refereed)
    Abstract [en]

    Capability approach is hard to operationalize and capabilities are sometimes difficult to reduce into the individual level. We describe our approach to solve these problems paired with an adequate ICT infrastructure and believe that the impact of concrete eGovernment services will become more visible and available. Citizens can inspect it, professionals can target their re-engineering on failure cases, learn from best cases, and researchers can compare different types of eGovernment. The solving of operationalisation will also strengthen the capability approach, by extending its scope from macro theory towards more easy application on the institutional and organizational levels.

  • 49.
    Islam, Raihan Ul
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Hossain, Mohammad Shahadat
    University of Chittagong.
    A Web Based Belief Rule Based Expert System to Predict Flood2015In: Proceedings of the 17th International Conference on Information Integration and Web-based Applications & Services (iiWAS2015) / [ed] Maria Indrawan-Santiago; Matthias Steinbauer; Ismail Khalil; Gabriele Anderst-Kotsis, New York: Association for Computing Machinery (ACM), 2015, p. 19-26, article id 3Conference paper (Refereed)
    Abstract [en]

    Natural calamity disrupts our daily life and brings many sufferings in our life. Among the natural calamities, flood is one of the most catastrophic. Predicting flood helps us to take necessary precautions and save human lives. Several types of data (meteorological condition, topography, river characteristics, and human activities) are used to predict flood water level in an area. In our previous works, we proposed a belief rule based flood prediction system in a desktop environment. In this paper, we propose a web-service based flood prediction expert system by incorporating belief rule base with the capability of reading sensor data such as rainfall, river flow on real time basis. This will facilitate the monitoring of the various flood-intensifying factors, contributing in increasing the flood water level in an area. Eventually, the decision makers would able to take measures to control those factors and to reduce the intensity of flooding in an area.

  • 50.
    Booth, Todd
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Elimination of DoS UDP Reflection Amplification Bandwidth Attacks, Protecting TCP Services2015In: Future Network Systems and Security: First International Conference, FNSS 2015, Paris, France, June 11-13, 2015, Proceedings / [ed] Robin Doss; Selwyn Piramuthu; Wei Zhou, Encyclopedia of Global Archaeology/Springer Verlag, 2015, p. 1-15Conference paper (Refereed)
    Abstract [en]

    In this paper, we propose a solution to eliminate a popular type of Denial of Service (DoS) attack, which is a DoS amplification attack. Note that a DoS is a subset of of DDoS. Our solution protects servers running any number of TCP services. This paper is focused on the most popular type of DoS amplification attack, which uses the UDP protocol. Via DoS UDP amplification attacks, an attacker can send a 1 Gbps traffic stream to reflectors. The reflectors will then send up 556 times that amount (amplified traffic) to the victim’s server. So just ten PCs, each sending 10Mbps, can send 55 Gbps indirectly, via reflectors, to a victim’s server. Very few ISP customers have 55 Gpbs provisioned. Expensive and complex solutions exist. However our elimination techniques can be implemented very quickly, easily and at an extremely low cost.

123 1 - 50 of 127
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