Change search
Refine search result
1 - 48 of 48
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Abd-Ellah, Mahmoud Khaled
    et al.
    Al-Madina Higher Institute for Engineering and Technology.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Khalaf, Ashraf A. M.
    Minia University, Egypt.
    Hamed, Hesham F. A.
    Minia University, Egypt.
    Classification of Brain Tumor MRIs Using a Kernel Support Vector Machine2016In: Building Sustainable Health Ecosystems: 6th International Conference on Well-Being in the Information Society, WIS 2016, Tampere, Finland, September 16-18, 2016, Proceedings / [ed] Hongxiu Li, Pirkko Nykänen, Reima Suomi, Nilmini Wickramasinghe, Gunilla Widén, Ming Zhan, Springer International Publishing , 2016, p. 151-160Conference paper (Refereed)
    Abstract [en]

    The use of medical images has been continuously increasing, which makes manual investigations of every image a difficult task. This study focuses on classifying brain magnetic resonance images (MRIs) as normal, where a brain tumor is absent, or as abnormal, where a brain tumor is present. A hybrid intelligent system for automatic brain tumor detection and MRI classification is proposed. This system assists radiologists in interpreting the MRIs, improves the brain tumor diagnostic accuracy, and directs the focus toward the abnormal images only. The proposed computer-aided diagnosis (CAD) system consists of five steps: MRI preprocessing to remove the background noise, image segmentation by combining Otsu binarization and K-means clustering, feature extraction using the discrete wavelet transform (DWT) approach, and dimensionality reduction of the features by applying the principal component analysis (PCA) method. The major features were submitted to a kernel support vector machine (KSVM) for performing the MRI classification. The performance evaluation of the proposed system measured a maximum classification accuracy of 100 % using an available MRIs database. The processing time for all processes was recorded as 1.23 seconds. The obtained results have demonstrated the superiority of the proposed system.

  • 2.
    Abd-Ellah, Mahmoud Khaled
    et al.
    Electronic and Communication Department Al-Madina Higher Institute for Engineering and Technology, Giza.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Khalaf, Ashraf A. M.
    Faculty of Engineering, Minia University.
    Hamed, Hesham F. A.
    Faculty of Engineering, Minia University.
    Design and implementation of a computer-aided diagnosis system for brain tumor classification2017In: 2016 28th International Conference on Microelectronics (ICM), 2017, p. 73-76, article id 7847911Conference paper (Refereed)
    Abstract [en]

    Computer-aided diagnosis (CAD) systems have become very important for the medical diagnosis of brain tumors. The systems improve the diagnostic accuracy and reduce the required time. In this paper, a two-stage CAD system has been developed for automatic detection and classification of brain tumor through magnetic resonance images (MRIs). In the first stage, the system classifies brain tumor MRI into normal and abnormal images. In the second stage, the type of tumor is classified as benign (Noncancerous) or malignant (Cancerous) from the abnormal MRIs. The proposed CAD ensembles the following computational methods: MRI image segmentation by K-means clustering, feature extraction using discrete wavelet transform (DWT), feature reduction by applying principal component analysis (PCA). The two-stage classification has been conducted using a support vector machine (SVM). Performance evaluation of the proposed CAD has achieved promising results using a non-standard MRIs database.

  • 3.
    Ali, Bako
    et al.
    Luleå University of Technology.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Faculty of Engineering, Al Azhar University.
    Cyber and Physical Security Vulnerability Assessment for IoT-Based Smart Homes2018In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, no 3, article id 817Article in journal (Refereed)
    Abstract [en]

     The Internet of Things (IoT) is an emerging paradigm focusing on the connection of devices, objects, or “things” to each other, to the Internet, and to users. IoT technology is anticipated to become an essential requirement in the development of smart homes, as it offers convenience and efficiency to home residents so that they can achieve better quality of life. Application of the IoT model to smart homes, by connecting objects to the Internet, poses new security and privacy challenges in terms of the confidentiality, authenticity, and integrity of the data sensed, collected, and exchanged by the IoT objects. These challenges make smart homes extremely vulnerable to different types of security attacks, resulting in IoT-based smart homes being insecure. Therefore, it is necessary to identify the possible security risks to develop a complete picture of the security status of smart homes. This article applies the operationally critical threat, asset, and vulnerability evaluation (OCTAVE) methodology, known as OCTAVE Allegro, to assess the security risks of smart homes. The OCTAVE Allegro method focuses on information assets and considers different information containers such as databases, physical papers, and humans. The key goals of this study are to highlight the various security vulnerabilities of IoT-based smart homes, to present the risks on home inhabitants, and to propose approaches to mitigating the identified risks. The research findings can be used as a foundation for improving the security requirements of IoT-based smart homes.

  • 4.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Workshop on Emerging Aspects in Information Security2015Other (Other (popular science, discussion, etc.))
  • 5.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Communications in Computer and Information Science, Vol. 3812013Other (Other (popular science, discussion, etc.))
  • 6.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Computer Networks2011Other (Other (popular science, discussion, etc.))
    Abstract [en]

    The International Journal of Computer and Telecommunications Networking (COMNET)

  • 7.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Computers & Security2014Other (Other (popular science, discussion, etc.))
  • 8.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Concurrency and Computation: Practice and Experience2016Other (Other (popular science, discussion, etc.))
  • 9.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Health Information Science and Systems (HISS)2016Other (Other (popular science, discussion, etc.))
  • 10.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Information Sciences2013Other (Other (popular science, discussion, etc.))
  • 11.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Intelligent Systems Reference Library, Vol. 702014Other (Other (popular science, discussion, etc.))
  • 12.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: International Conference on Mobile and Ubiquitous Systems2013Other (Other (popular science, discussion, etc.))
  • 13.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: International Conference on Telecommunications2016Other (Other (popular science, discussion, etc.))
  • 14.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: International Conference on Telecommunications2016Other (Other (popular science, discussion, etc.))
  • 15.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: International Japan-Egypt Conference on Electronics, Communications and Computers2013Other (Other (popular science, discussion, etc.))
  • 16.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: International Journal of Computational Vision and Robotics. Special Issue on: "Advances in Soft Computing Techniques for Image Processing"2013Other (Other (popular science, discussion, etc.))
    Abstract [en]

    Vol. 3, No. 4

  • 17.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Pattern Recognition2014Other (Other (popular science, discussion, etc.))
    Abstract [en]

    The Journal of the Pattern Recognition Society

  • 18.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Science and Information Conference2014Other (Other (popular science, discussion, etc.))
  • 19.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Science and Information Conference2013Other (Other (popular science, discussion, etc.))
  • 20.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: SpringerPlus2015Other (Other (popular science, discussion, etc.))
  • 21.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Studies in Computational Intelligence, Vol. 6302016Other (Other (popular science, discussion, etc.))
  • 22.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: The 28th International Conference on Image and Vision Computing New Zealand (IVCNZ 2013)2013Other (Other (popular science, discussion, etc.))
  • 23.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: The 29th International Conference on Image and Vision Computing New Zealand (IVCNZ 2014)2014Other (Other (popular science, discussion, etc.))
  • 24.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: The 30th International Conference on Image and Vision Computing New Zealand ( (IVCNZ 2015)2015Other (Other (popular science, discussion, etc.))
  • 25.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: The 31st International Conference Image and Vision Computing New Zealand (IVCNZ 2016)2016Other (Other (popular science, discussion, etc.))
  • 26.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: The 49th Hawaii International Conference on System Sciences (HICSS-49)2016Other (Other (popular science, discussion, etc.))
  • 27.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Aktivitet: Workshop on Emerging Aspects in Information Security2014Other (Other (popular science, discussion, etc.))
  • 28.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Erratum to : Fast Fingerprint Orientation Field Estimation Incorporating General Purpose GPU2016In: Soft Computing Applications: Proceedings of the 6th International Workshop Soft Computing Applications (SOFA 2014) / [ed] Valentina Emilia Balas; Lakhmi C. Jain; Branko Kovačević, New York: Encyclopedia of Global Archaeology/Springer Verlag, 2016, Vol. 2, p. E1-Conference paper (Refereed)
    Abstract [en]

    Fingerprint is one of the broadly utilized biometric traits for personal identification in both civilian and forensic applications due to its high acceptability, strong security, and low cost. Fingerprint ridge orientation is one of the global fingerprint representations that keeps the holistic ridge structure in a small storage area. The importance of fingerprint ridge orientation comes from its usage in fingerprint singular point detection, coarse level classification, and fingerprint alignment. However, processing time is an important factor in any automatic fingerprint identification system, estimating that ridge orientation image may consume long processing time. This research presents an efficient ridge orientation estimation approach by incorporating a Graphics Processing Unit (GPU) capability to the traditional pixel gradient method. The simulation work shows a significant enhancement in ridge orientation estimation time by 6.41x using a general purpose GPU in comparison to the CPU execution.

  • 29.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Fast Fingerprint Orientation Field Estimation Incorporating General Purpose GPU2016In: Soft Computing Applications: Proceedings of the 6th International Workshop Soft Computing Applications (SOFA 2014) / [ed] Valentina Emilia Balas; Lakhmi C. Jain; Branko Kovačević, New York: Encyclopedia of Global Archaeology/Springer Verlag, 2016, Vol. 2, p. 891-902Conference paper (Refereed)
    Abstract [en]

    Fingerprint is one of the broadly utilized biometric traits for personal identification in both civilian and forensic applications due to its high acceptability, strong security, and low cost. Fingerprint ridge orientation is one of the global fingerprint representations that keeps the holistic ridge structure in a small storage area. The importance of fingerprint ridge orientation comes from its usage in fingerprint singular point detection, coarse level classification, and fingerprint alignment. However, processing time is an important factor in any automatic fingerprint identification system, estimating that ridge orientation image may consume long processing time. This research presents an efficient ridge orientation estimation approach by incorporating a Graphics Processing Unit (GPU) capability to the traditional pixel gradient method. The simulation work shows a significant enhancement in ridge orientation estimation time by 6.41x using a general purpose GPU in comparison to the CPU execution.

  • 30.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Fingerprint local invariant feature extraction on GPU with CUDA2013In: Informatica, ISSN 0350-5596, E-ISSN 1854-3871, Vol. 37, no 3, p. 279-284Article in journal (Refereed)
    Abstract [en]

    Driven from its uniqueness, immutability, acceptability, and low cost, fingerprint is in a forefront between biometric traits. Recently, the GPU has been considered as a promising parallel processing technology due to its high performance computing, commodity, and availability. Fingerprint authentication is keep growing, and includes the deployment of many image processing and computer vision algorithms. This paper introduces the fingerprint local invariant feature extraction using two dominant detectors, namely SIFT and SURF, which are running on the CPU and the GPU. The paper focuses on the consumed time as an important factor for fingerprint identification. The experimental results show that the GPU implementations produce promising behaviors for both SIFT and SURF compared to the CPU one. Moreover, the SURF feature detector provides shorter processing time compared to the SIFT CPU and GPU implementations.

  • 31.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    From classical methods to animal biometrics: A review on cattle identification and tracking2016In: Computers and Electronics in Agriculture, ISSN 0168-1699, E-ISSN 1872-7107, Vol. 123, p. 423-435Article in journal (Refereed)
    Abstract [en]

    Cattle, buffalo and cow, identification has recently played an influential role towards understanding disease trajectory, vaccination and production management, animal traceability, and animal ownership assignment. Cattle identification and tracking refers to the process of accurately recognizing individual cattle and their products via a unique identifier or marker. Classical cattle identification and tracking methods such as ear tags, branding, tattooing, and electrical methods have long been in use; however, their performance is limited due to their vulnerability to losses, duplications, fraud, and security challenges. Owing to their uniqueness, immutability, and low costs, biometric traits mapped into animal identification systems have emerged as a promising trend. Biometric identifiers for beef animals include muzzle print images, iris patterns, and retinal vascular patterns. Although using biometric identifiers has replaced human experts with computerized systems, it raises additional challenges in terms of identifier capturing, identification accuracy, processing time, and overall system operability. This article reviews the evolution in cattle identification and tracking from classical methods to animal biometrics. It reports on traditional animal identification methods and their advantages and problems. Moreover, this article describes the deployment of biometric identifiers for effectively identifying beef animals. The article presents recent research findings in animal biometrics, with a strong focus on cattle biometric identifiers such as muzzle prints, iris patterns, and retinal vascular patterns. A discussion of current challenges involved in the biometric-based identification systems appears in the conclusions, which may drive future research directions.

  • 32.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Introduction to Information Security Foundations and Applications2018In: Information Security: Foundations, technologies and applications / [ed] Ali Ismail Awad and Michael Fairhurst, Institution of Engineering and Technology, 2018, , p. 432p. 3-9Chapter in book (Refereed)
  • 33.
    Awad, Ali Ismail
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andrzej, BialasInstitute of Innovative Technologies EMAG.
    Proceedings of the 2017 Federated Conference on Computer Science and Information Systems (FedCSIS 2017)2017Conference proceedings (editor) (Refereed)
    Abstract [en]

    https://fedcsis.org/2017/insert

  • 34.
    Awad, Ali Ismail
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hassanien, Aboul Ella
    Cairo University.
    Erratum: Impact of Some Biometric Modalities on Forensic Science2014In: Computational Intelligence in Digital Forensics: Forensic Investigation and Applications, Switzerland: Springer International Publishing , 2014, p. E1-Chapter in book (Refereed)
  • 35.
    Awad, Ali Ismail
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hassanien, Aboul Ella
    Faculty of Computers and Information, Cairo University.
    Impact of Some Biometric Modalities on Forensic Science2014In: Computational Intelligence in Digital Forensics: Forensic Investigation and Applications, Springer International Publishing , 2014, p. 47-62Chapter in book (Refereed)
    Abstract [en]

    Recently, forensic science has had many challenges in many different types of crimes and crime scenes, vary from physical crimes to cyber or computer crimes. Accurate and efficient human identification or recognition have become crucial for forensic applications due to the large diversity of crime scenes, and because of the increasing need to accurately identify criminals from the available crime evidences. Biometrics is an emerging technology that provides accurate and highly secure personal identification and verification systems for civilian and forensic applications. The positive impact of biometric modalities on forensic science began with the rapid developments in computer science, computational intelligence, and computing approaches. These advancements have been reflected in the biometric modality capturing process, feature extraction, feature robustness, and features matching. A complete and automatic biometric identification or recognition systems have been built accordingly. This chapter presents a study of the impacts of using some biometric modalities in forensic applications. Although biometrics identification replaces human work with computerized and automatic systems in order to achieve better performance, new challenges have arisen. These challenges lie in biometric system reliability and accuracy, system response time, data mining and classification, and protecting user privacy. This chapter sheds light on the positive and the negative impacts of using some biometric modalities in forensic science. In particular, the impacts of fingerprint image, facial image, and iris patterns are considered. The selected modalities are covered preliminarily before tackling their impact on forensic applications. Furthermore, an extensive look at the future of biometric modalities deployment in forensic applications is covered as the last part of the chapter.

  • 36.
    Charif, Bilal
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Business and Government Organizations' Adoption of Cloud Computing2014In: Intelligent Data Engineering and Automated Learning – IDEAL 2014: 15th International Conference, Salamanca, Spain, September 10-12, 2014, Proceedings / [ed] Emilio Corchado; José A. Lozano; Héctor Quintián; Hujun Yin, Switzerland: Springer International Publishing , 2014, p. 492-501Conference paper (Refereed)
    Abstract [en]

    Cloud computing is very much accepted and acknowledged worldwide as a promising computing paradigm. On-demand provisioning based on a pay-per-use business model helps reduce costs through sharing computing and storage resources. Although cloud computing has become popular, some business and government organizations are still lagging behind in adopting cloud computing. This study reports the status of cloud utilization among business and government organizations, and the concerns of organizations regarding the adoption of cloud computing. The study shows that some government agencies are lagging behind in cloud computing use, while others are leading the way. Security is identified as the major reason for delay in adopting cloud computing. The outcomes of the data analysis process prove that some security measures such as encryption, access authentication, antivirus protection, firewall, and service availability are required by clients for adoption of cloud computing in the future.

  • 37.
    Charif, Bilal
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Towards smooth organisational adoption of cloud computing: a customer-provider security adaptation2016In: Computer fraud & security, ISSN 1361-3723, E-ISSN 1873-7056, Vol. 2016, no 2, p. 7-15Article in journal (Refereed)
    Abstract [en]

    Cloud computing is daily becoming more and more accepted as a promising computing paradigm. For some years now, cloud computing has been in common use for such applications as Google apps (email, documents, etc), MSN Messenger (instant messaging), Skype (voice communications), and Flickr (image sharing). The idea of offering cloud computing facilities as a public utility began as early as the 1960s with John McCarthy.1, 2, 3 and 4 Organisations and universities offered distributed computing starting in the late 1970s through dial-up access.5 Grid computing was introduced in the early 1990s with the idea of providing access to shared computing power similar to the way electricity is shared through the electric power grid. In addition, open source platforms were first introduced by Eucalyptus, OpenNebula, and Nimbus for deploying private and hybrid clouds.6, 7 and 8Although cloud computing has been available for some time, there is still some organisational resistance to its adoption, not least because of security concerns.Bilal Charif, of Luleå University of Technology, Sweden and Ali Ismail Awad of Luleå University and Al Azhar University, Egypt show that a number of organisations have no internal security responsibilities, nor do they have proper information security policies such as business and disaster recovery plans, all of which makes cloud adoption difficult. In contrast, cloud computing offers recovery plans for small and medium-sized organisations that will often otherwise not be implemented.

  • 38.
    Elrawy, Mohammed Faisal
    et al.
    MUST University, 6th of October.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hamed, Hesham F. A.
    Minia University, Egypt.
    Flow-based Features for a Robust Intrusion Detection System Targeting Mobile Traffic2016In: 23rd International Conference on Telecommunications (ICT): Thessaloniki, 16-18 May 2016, Piscataway, NJ: IEEE Communications Society, 2016, article id 7500483Conference paper (Refereed)
    Abstract [en]

    The security risks and threats that impact wired and wireless networks are now applicable to mobile telecommunication networks. Threat detection systems should be more intelligent because threats are becoming more dangerous. An intrusion detection system (IDS) is a potential network security solution for protecting the confidentiality, integrity, and availability of user data and information resources. A fast and effective IDS for mobile networks that does not violate the user's privacy or the network's QoS is required. This paper offers a set of flow-based features that can be utilized for mobile network traffic as a prerequisite for a privacy-aware and QoS-robust IDS. The principal component analysis (PCA) method was used for reduction of the features. Twelve features in six groups, which represent the user data in mobile traffic, were extracted and evaluated for IDSs. The evaluation process achieved a F-measure weighted average equal to 0.834, and the experimental time was equal to 12.9 seconds. The accomplished measurements have demonstrated the applicability of the proposed set of features.

  • 39.
    Grzenda, Maciej
    et al.
    Faculty of Mathematics and Information Science, Warsaw University of Technology,, Research and Development Center.
    Furtak, Janusz
    Military University of Technology, Warszawa.
    Legierski, Jarosław
    Faculty of Mathematics and Information Science, Warsaw University of Technology, Warszawa.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Network Architectures, Security, and Applications: An Introduction2017In: Advances in Network Systems: Architectures, Security, and Applications / [ed] Maciej Grzenda, Ali Ismail Awad, Janusz Furtak, Jarosław Legierski, Berlin: Springer Berlin/Heidelberg, 2017, p. 1-10Chapter in book (Refereed)
    Abstract [en]

    Owing to the ever growing communication systems, modern networks currently encompass a wide range of solutions and technologies, including wireless and wired networks and provide basis for network systems from multiple partly overlapping domains such as the Internet of Things (IoT), cloud services, and network applications. This appears in numerous active research areas with particular attention paid to the architecture and security of network systems. In parallel, novel applications are developed, in some cases strongly linked to rapidly developing network-based data acquisition and processing frameworks. This chapter presents a general introduction to the topics of network architectures, security, and applications in addition to short descriptions of the chapters included in this volume

  • 40.
    Hassaballah, Mahmoud
    et al.
    Image and Video Processing Lab, Faculty, South Valley University.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Detection and Description of Image Features: An Introduction2016In: Image Feature Detectors and Descriptors: Foundations and Applications, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 1-8Chapter in book (Refereed)
    Abstract [en]

    Detection and description of image features play a vital role in various application domains such as image processing, computer vision, pattern recognition, and machine learning. There are two type of features that can be extracted from an image content; namely global and local features. Global features describe the image as a whole and can be interpreted as a particular property of the image involving all pixels; while, the local features aim to detect keypoints within the image and describe regions around these keypoints. After extracting the features and their descriptors from images, matching of common structures between images (i.e., features matching) is the next step for these applications. This chapter presents a general and brief introduction to topics of feature extraction for a variety of application domains. Its main aim is to provide short descriptions of the chapters included in this book volume.

  • 41.
    Hassan, Abbas M.
    et al.
    Department of Architecture, Faculty of Engineering, Al Azhar University .
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Electrical Engineering Department, Faculty of Engineering, Al Azhar University.
    Urban Transition in the Era of the Internet of Things: Social Implications and Privacy Challenges2018In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 36428-36440Article in journal (Refereed)
    Abstract [en]

    The Internet of Things (IoT) could become an important aspect of urban life in the next decade. In the IoT paradigm, various information and communication technologies (ICTs) are used in concert to substantially reduce urban problems. Smart cities and ubiquitous cities will adopt ICTs in the urban development process; however, IoT-based cities will experience considerably stronger effects than those that adopt conventional ICTs. IoT cities allow urban residents and “things”to be connected to the Internet by virtue of the extension of the Internet Protocol from IPv4 to IPv6 and of cutting-edge device and sensor technology. Therefore, the urban transition resulting from the influence of IoT may be a critical issue. The privacy-related vulnerabilities of IoT technologies may negatively affect city residents. Furthermore, disparities in the spread of IoT systems across different countries may allow some countries to subvert the privacy of other countries' citizens. The aim of this paper is to identify the potential prospects and privacy challenges that will emerge from IoT deployment in urban environments. This paper reviews the prospects of and barriers to IoT implementation at the regional, city, and residential scales from the perspectives of security and privacy. The IoT technology will be a continual presence in life in general and in urban life in particular. However, the adoption of the IoT paradigm in cities will be complicated due to the inherent presence of unsecured connections. Moreover, the IoT systems may rob people of some of their humanity, infringing on their privacy, because people are also regarded as “things”in the IoT paradigm. Given the social trepidation surrounding IoT implementation, local and international associations related to IoT privacy, and legislation and international laws, are needed to maintain the personal right to privacy and to satisfy the demands of institutional privacy in urban contexts.

  • 42.
    Hemanth, D. Jude
    Department of Electronics and Communication Engineering, Karunya University.
    Editorial: Special Issue on: Advances in Soft Computing Techniques for Image Processing2013In: International Journal of Computational Vision and Robotics, ISSN 1752-9131, Vol. 3, no 4, p. 249-250Article in journal (Refereed)
  • 43.
    Iqbal, Sarfraz
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Thapa, Devinder
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Design Principles for online Information Security laboratory2014In: Selected Papers of the Information Systems Research Seminar in Scandinavia, 2014, p. 65-79Conference paper (Refereed)
    Abstract [en]

    In this paper, we reported an online InfoSec Lab based on initial design principles derived from kernel theories such as Conversational Framework (CF), Constructive Alignment (CA), and Personalized System of Instruction (PSI). The overall research was conducted using the action design research approach. In doing so, the iterative cycles and critical reflections during the process helped to refine a set of existing design principles. The study contributes to the IS community by providing design principles for an online InfoSec Lab that utilizes state-of-the art technology for mixed classrooms.

  • 44.
    Iqbal, Sarfraz
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Thapa, Devinder
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Päivärinta, Tero
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Conceptual Model of Online Pedagogical Information Security Laboratory: Toward an Ensemble Artifact2015In: 2015 48th Hawaii International Conference on System Sciences (HICSS 2015): Hawaii, USA, 5-8 January 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 43-52, article id 7069664Conference paper (Refereed)
    Abstract [en]

    Distance education in information security has unique requirements in comparison to on-campus education. For instance, an online InfoSec lab is required to provide hands-on education to distance students while development and operation of a lab is a non-trivial problem. There is a need to understand the nature of the online InfoSec labs as ensemble artifacts, and just a black-box tool’s view is not enough. This article suggests a conceptual model to explain the ensemble view of the online InfoSec lab. In doing so, the paper makes two specific contributions: First, it conceptualizes the online Information Security (InfoSec) lab as an ensemble artifact so that we can unfold the black-box view of an InfoSec lab and understand the important building blocks (entities of the lab) and their interrelationships. Second, it suggests design principles to implement the conceptual model of an InfoSec lab.

  • 45.
    King, James
    et al.
    Luleå University of Technology.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Distributed Security Mechanism for Resource-Constrained IoT Devices2016In: Informatica, ISSN 0350-5596, E-ISSN 1854-3871, Vol. 40, no 1, p. 133-143Article in journal (Refereed)
    Abstract [en]

    Internet of Things (IoT) devices have developed to comprise embedded systems and sensors with the ability to connect, collect, and transmit data over the Internet. Although solutions to secure IoT systems exist, Class-0 IoT devices with insufficient resources to support such solutions are considered a resource constrained in terms of secure communication. This paper provides a distributed security mechanism that targets Class-0 IoT devices. The research goal is to secure the entire data path in two segments, device-to-gateway and gateway-to-server data communications. The main concern in the provided solution is that lighter security operations with minimal resource requirements are performed in the IoT device, while heavier tasks are performed in the gateway side. The proposed mechanism utilizes a symmetric encryption for data objects combined with the native wireless security to offer a layered security technique between the device and the gateway. In the offered solution, the IoT gateways provide additional protection by securing data using Transport Layer Security (TLS). Real-time experimental evaluations have demonstrated the applicability of the proposed mechanism pertaining to the security assurance and the consumed resources of the target Class-0 IoT devices.

  • 46.
    Okoh, Ebenezer
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Biometrics Applications in e-Health Security: A Preliminary Survey2015In: Health Information Science: 4th International Conference, HIS 2015, Melbourne, Australia, May 28-30, 2015, Proceedings / [ed] Xiaoxia Yin; Kendall Ho; Daniel Zeng; Uwe Aickelin; Rui Zhou; Hua Wang, Encyclopedia of Global Archaeology/Springer Verlag, 2015, p. 92-103Conference paper (Refereed)
    Abstract [en]

    Driven by the desires of healthcare authorities to offer better healthcare services at a low cost, electronic Health (e-Health) has revolutionized the healthcare industry. However, while e-Health comes with numerous advantages that improve health services, it still suffers from security and privacy issues in handling health information. E-Health security issues are mainly centered around user authentication, data integrity, data confidentiality, and patient privacy protection. Biometrics technology addresses the above security problems by providing reliable and secure user authentication compared to the traditional approaches. This study explores the security and privacy issues in e-Health, and offers a comprehensive overview of biometrics technology applications in addressing the e-Health security challenges. The paper concludes that biometrics technology has considerable opportunities for application in e-Health due to its ability to provide reliable security solutions. Although, additional issues like system complexity, processing time, and patient privacy related to the use of biometrics should be taken into consideration.

  • 47.
    Okoh, Ebenezer
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Makame, Hamza Makame
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Awad, Ali Ismail
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Toward online education for fingerprint recognition: A proof-of-concept web platform2017In: Information Security Journal, ISSN 1939-3555, E-ISSN 1939-3547, Vol. 26, no 4, p. 186-197Article in journal (Refereed)
    Abstract [en]

    Recent advances in information and communication technology (ICT) have pushed education systems into the online paradigm. Although fingerprint recognition has received considerable attention from researchers, the concept of creating online or distance education systems for fingerprint recognition systems is a valid problem that requires further investigation. This article addresses the problem and presents a web platform for online education of a fingerprint recognition system. This study focused on the technical design and implementation of the web platform solely as a proof of concept to illustrate the possibility of creating distance education for fingerprint recognition. The developed platform offers students a way to gain knowledge about the full range of fingerprint recognition system technology. The significance of using a web platform stems from the need to supplement students’ theoretical knowledge with practical hands-on experience with information security in general and with fingerprint recognition in particular. Demonstrations such as fingerprint image enhancement and fingerprint feature extraction are included in the current platform prototype. Plots of fingerprint recognition performance curves such as false match rate (FMR) and false non-match rate (FNMR) as functions of the matching threshold curve, the receiver operating characteristic (ROC) curve, and the detection error trade-off (DET) curve are plotted as part of the platform. From a technical viewpoint, the platform was successfully implemented; however, its educational impact needs further evaluation.

  • 48.
    Awad, Ali Ismail (Editor)
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Electrical Engineering Department, Faculty of Engineering, Al Azhar University, Qena.
    Fairhurst, Michael (Editor)
    School of Engineering and Digital Arts at the University of Kent.
    Information Security: Foundations, technologies and applications2018Book (Refereed)
1 - 48 of 48
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf