Ändra sökning
Avgränsa sökresultatet
12 1 - 50 av 57
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Träffar per sida
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sortering
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
Markera
Maxantalet träffar du kan exportera från sökgränssnittet är 250. Vid större uttag använd dig av utsökningar.
  • 1.
    Abd-Ellah, Mahmoud Khaled
    et al.
    Electronics and Communications Department, Al-Madina Higher Institute for Engineering and Technology, Giza, Egypt.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap. Faculty of Engineering, Al-Azhar University, Qena, Egypt.
    Khalaf, Ashraf A.M.
    Electronics and Communications Department, Faculty of Engineering, Minia University, Minia, Egypt.
    Hamed, Hesham F.A.
    Electronics and Communications Department, Faculty of Engineering, Minia University, Minia, Egypt.
    A Review on Brain Tumor Diagnosis from MRI Images: Practical Implications, Key Achievements, and Lessons Learned2019Ingår i: Magnetic Resonance Imaging, ISSN 0730-725X, E-ISSN 1873-5894, Vol. 61, s. 300-318Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The successful early diagnosis of brain tumors plays a major role in improving the treatment outcomes and thus improving patient survival. Manually evaluating the numerous magnetic resonance imaging (MRI) images produced routinely in the clinic is a difficult process. Thus, there is a crucial need for computer-aided methods with better accuracy for early tumor diagnosis. Computer-aided brain tumor diagnosis from MRI images consists of tumor detection, segmentation, and classification processes. Over the past few years, many studies have focused on traditional or classical machine learning techniques for brain tumor diagnosis. Recently, interest has developed in using deep learning techniques for diagnosing brain tumors with better accuracy and robustness. This study presents a comprehensive review of traditional machine learning techniques and evolving deep learning techniques for brain tumor diagnosis. This review paper identifies the key achievements reflected in the performance measurement metrics of the applied algorithms in the three diagnosis processes. In addition, this study discusses the key findings and draws attention to the lessons learned as a roadmap for future research.

  • 2.
    Awad, Ali Ismail
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Furnell, Steven
    Centre for Security, Communications & Network Research, Plymouth University.
    Hassan, Abbas M.
    Faculty of Engineering, Qena, Al-Azhar University, Egypt.
    Tryfonas, Theo
    University of Bristol, United Kingdom.
    Special issue on security of IoT-enabled infrastructures in smart cities2019Ingår i: Ad hoc networks, ISSN 1570-8705, E-ISSN 1570-8713, Vol. 83Artikel i tidskrift (Refereegranskat)
  • 3.
    Ali, Bako
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap. Faculty of Engineering, Al Azhar University.
    Cyber and Physical Security Vulnerability Assessment for IoT-Based Smart Homes2018Ingår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, nr 3, artikel-id 817Artikel i tidskrift (Refereegranskat)
    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 (Redaktör)
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap. Electrical Engineering Department, Faculty of Engineering, Al Azhar University, Qena.
    Fairhurst, Michael (Redaktör)
    School of Engineering and Digital Arts at the University of Kent.
    Information Security: Foundations, technologies and applications2018Bok (Refereegranskat)
  • 5.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Introduction to Information Security Foundations and Applications2018Ingår i: Information Security: Foundations, technologies and applications / [ed] Ali Ismail Awad and Michael Fairhurst, Institution of Engineering and Technology, 2018, , s. 432s. 3-9Kapitel i bok, del av antologi (Refereegranskat)
  • 6.
    Elrawy, Mohamed Faisal
    et al.
    Department of Electronics and Communication Engineering, MUST University, 6th of October, Egypt; Institute of Public Administration, Abha, Asir, Saudi Arabia.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap. Faculty of Engineering, Al-Azhar University, Qena, P.O. Box 83513, Egypt.
    Hamed, Hesham F. A.
    Faculty of Engineering, Minia University, Minia, Egypt.
    Intrusion detection systems for IoT-based smart environments: a survey2018Ingår i: Journal of Cloud Computing - Advances, Systems and Applications, ISSN 2192-113X, Vol. 7, nr 21, s. 1-20Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    One of the goals of smart environments is to improve the quality of human life in terms of comfort and efficiency. The Internet of Things (IoT) paradigm has recently evolved into a technology for building smart environments. Security and privacy are considered key issues in any real-world smart environment based on the IoT model. The security vulnerabilities in IoT-based systems create security threats that affect smart environment applications. Thus, there is a crucial need for intrusion detection systems (IDSs) designed for IoT environments to mitigate IoT-related security attacks that exploit some of these security vulnerabilities. Due to the limited computing and storage capabilities of IoT devices and the specific protocols used, conventional IDSs may not be an option for IoT environments. This article presents a comprehensive survey of the latest IDSs designed for the IoT model, with a focus on the corresponding methods, features, and mechanisms. This article also provides deep insight into the IoT architecture, emerging security vulnerabilities, and their relation to the layers of the IoT architecture. This work demonstrates that despite previous studies regarding the design and implementation of IDSs for the IoT paradigm, developing efficient, reliable and robust IDSs for IoT-based smart environments is still a crucial task. Key considerations for the development of such IDSs are introduced as a future outlook at the end of this survey.

  • 7.
    Munodawafa, Fortune
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap. Faculty of Engineering, Al-Azhar University, Qena, Egypt.
    Security risk assessment within hybrid data centers: a case study of delay sensitive applications2018Ingår i: Journal of Information Security and Applications, ISSN 2214-2134, E-ISSN 2214-2126, Vol. 43, s. 61-72Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Data centers are considered a critical form of infrastructure in today’s information society. They are at the core of the cloud computing and services revolution, which has changed the business models on how organizations deal with IT infrastructure costs. The hybrid data center architecture incorporates both legacy and fully virtualized infrastructures. On the one hand, the composite infrastructure has improved resource utilization and consolidation by adding flexibility and scalability factors, making the data center more cost effective and more agile. On the other hand, the hybrid infrastructure has imposed a new set of security challenges that need to be brought into focus. The lack of resource availability can be a great risk for delay sensitive applications such as voice over IP (VoIP) and online gaming when cloud computing is the deployment model. This study addresses the emerging risk problem by conducting a comprehensive security risk assessment using the NIST national vulnerability database (NVD) combined with EBIOS risk analysis and evaluation methodology. This study focuses on resource availability problem emanating from delay variations and queuing mechanisms in virtualized systems and its impact on delay sensitive applications. The study argues for the existence of availability risk within the hybrid data center infrastructure, which can deteriorate the performance of delay sensitive applications. Security remedial and countermeasures to the identified security risks are suggested in an extended discussion at the end of the study.

  • 8.
    Khaled Abd-Ellah, Mahmoud
    et al.
    Electronic and Communication Department, Al-Madina Higher Institute for Engineering and Technology, Giza, Egypt.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap. Faculty of Engineering, Al-Azhar University, Qena, P.O. Box 83513, Egypt.
    Khalaf, Ashraf A. M.
    Faculty of Engineering, Minia University, Minia, Egypt.
    Hamed, Hesham F. A.
    Faculty of Engineering, Minia University, Minia, Egypt.
    Two-phase multi-model automatic brain tumour diagnosis system from magnetic resonance images using convolutional neural networks2018Ingår i: EURASIP Journal on Image and Video Processing, ISSN 1687-5176, E-ISSN 1687-5281, Vol. 2018, artikel-id 97Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Brain tumour is a serious disease, and the number of people who are dying due to brain tumours is increasing. Manual tumour diagnosis from magnetic resonance images (MRIs) is a time consuming process and is insufficient for accurately detecting, localizing, and classifying the tumour type. This research proposes a novel two-phase multi-model automatic diagnosis system for brain tumour detection and localization. In the first phase, the system structure consists of preprocessing, feature extraction using a convolutional neural network (CNN), and feature classification using the error-correcting output codes support vector machine (ECOC-SVM) approach. The purpose of the first system phase is to detect brain tumour by classifying the MRIs into normal and abnormal images. The aim of the second system phase is to localize the tumour within the abnormal MRIs using a fully designed five-layer region-based convolutional neural network (R-CNN). The performance of the first phase was assessed using three CNN models, namely, AlexNet, Visual Geometry Group (VGG)-16, and VGG-19, and a maximum detection accuracy of 99.55% was achieved with AlexNet using 349 images extracted from the standard Reference Image Database to Evaluate Response (RIDER) Neuro MRI database. The brain tumour localization phase was evaluated using 804 3D MRIs from the Brain Tumor Segmentation (BraTS) 2013 database, and a DICE score of 0.87 was achieved. The empirical work proved the outstanding performance of the proposed deep learning-based system in tumour detection compared to other non-deep-learning approaches in the literature. The obtained results also demonstrate the superiority of the proposed system concerning both tumour detection and localization.

  • 9.
    Hassan, Abbas M.
    et al.
    Department of Architecture, Faculty of Engineering, Al Azhar University .
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap. Electrical Engineering Department, Faculty of Engineering, Al Azhar University.
    Urban Transition in the Era of the Internet of Things: Social Implications and Privacy Challenges2018Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 6, s. 36428-36440Artikel i tidskrift (Refereegranskat)
    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.

  • 10.
    Grzenda, Maciej
    et al.
    Faculty of Mathematics and Information Science, Warsaw University of Technology,, Research and Development Center.
    Awad, Ali IsmailLuleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.Furtak, JanuszMilitary University of Technology, Warszawa.Legierski, JarosławFaculty of Mathematics and Information Science, Warsaw University of Technology, Warszawa.
    Advances in Network Systems: Architectures, Security, and Applications2017Samlingsverk (redaktörskap) (Refereegranskat)
  • 11.
    Abd-Ellah, Mahmoud Khaled
    et al.
    Electronic and Communication Department Al-Madina Higher Institute for Engineering and Technology, Giza.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    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 classification2017Ingår i: 2016 28th International Conference on Microelectronics (ICM), 2017, s. 73-76, artikel-id 7847911Konferensbidrag (Refereegranskat)
    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.

  • 12.
    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 tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Network Architectures, Security, and Applications: An Introduction2017Ingår i: Advances in Network Systems: Architectures, Security, and Applications / [ed] Maciej Grzenda, Ali Ismail Awad, Janusz Furtak, Jarosław Legierski, Berlin: Springer Berlin/Heidelberg, 2017, s. 1-10Kapitel i bok, del av antologi (Refereegranskat)
    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

  • 13.
    Awad, Ali Ismail
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Andrzej, BialasInstitute of Innovative Technologies EMAG.
    Proceedings of the 2017 Federated Conference on Computer Science and Information Systems (FedCSIS 2017)2017Proceedings (redaktörskap) (Refereegranskat)
    Abstract [en]

    https://fedcsis.org/2017/insert

  • 14.
    Okoh, Ebenezer
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Makame, Hamza Makame
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Toward online education for fingerprint recognition: A proof-of-concept web platform2017Ingår i: Information Security Journal, ISSN 1939-3555, E-ISSN 1939-3547, Vol. 26, nr 4, s. 186-197Artikel i tidskrift (Refereegranskat)
    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.

  • 15.
    King, James
    et al.
    Luleå University of Technology.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    A Distributed Security Mechanism for Resource-Constrained IoT Devices2016Ingår i: Informatica, ISSN 0350-5596, E-ISSN 1854-3871, Vol. 40, nr 1, s. 133-143Artikel i tidskrift (Refereegranskat)
    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.

  • 16.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: Concurrency and Computation: Practice and Experience2016Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 17.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: Health Information Science and Systems (HISS)2016Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 18.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: International Conference on Telecommunications2016Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 19.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: International Conference on Telecommunications2016Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 20.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: Studies in Computational Intelligence, Vol. 6302016Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 21.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: The 31st International Conference Image and Vision Computing New Zealand (IVCNZ 2016)2016Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 22.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: The 49th Hawaii International Conference on System Sciences (HICSS-49)2016Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 23.
    Abd-Ellah, Mahmoud Khaled
    et al.
    Al-Madina Higher Institute for Engineering and Technology.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Khalaf, Ashraf A. M.
    Minia University, Egypt.
    Hamed, Hesham F. A.
    Minia University, Egypt.
    Classification of Brain Tumor MRIs Using a Kernel Support Vector Machine2016Ingår i: 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, s. 151-160Konferensbidrag (Refereegranskat)
    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.

  • 24.
    Hassaballah, Mahmoud
    et al.
    Image and Video Processing Lab, Faculty, South Valley University.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Detection and Description of Image Features: An Introduction2016Ingår i: Image Feature Detectors and Descriptors: Foundations and Applications, Encyclopedia of Global Archaeology/Springer Verlag, 2016, s. 1-8Kapitel i bok, del av antologi (Refereegranskat)
    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.

  • 25.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Erratum to : Fast Fingerprint Orientation Field Estimation Incorporating General Purpose GPU2016Ingår i: 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, s. E1-Konferensbidrag (Refereegranskat)
    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.

  • 26.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Fast Fingerprint Orientation Field Estimation Incorporating General Purpose GPU2016Ingår i: 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, s. 891-902Konferensbidrag (Refereegranskat)
    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.

  • 27.
    Elrawy, Mohammed Faisal
    et al.
    MUST University, 6th of October.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hamed, Hesham F. A.
    Minia University, Egypt.
    Flow-based Features for a Robust Intrusion Detection System Targeting Mobile Traffic2016Ingår i: 23rd International Conference on Telecommunications (ICT): Thessaloniki, 16-18 May 2016, Piscataway, NJ: IEEE Communications Society, 2016, artikel-id 7500483Konferensbidrag (Refereegranskat)
    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.

  • 28.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    From classical methods to animal biometrics: A review on cattle identification and tracking2016Ingår i: Computers and Electronics in Agriculture, ISSN 0168-1699, E-ISSN 1872-7107, Vol. 123, s. 423-435Artikel i tidskrift (Refereegranskat)
    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.

  • 29.
    Awad, Ali Ismail
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hassaballah, MahmoudImage and Video Processing Lab, Faculty, South Valley University.
    Image Feature Detectors and Descriptors: Foundations and Applications2016Samlingsverk (redaktörskap) (Refereegranskat)
  • 30.
    Charif, Bilal
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Towards smooth organisational adoption of cloud computing: a customer-provider security adaptation2016Ingår i: Computer fraud & security, ISSN 1361-3723, E-ISSN 1873-7056, Vol. 2016, nr 2, s. 7-15Artikel i tidskrift (Refereegranskat)
    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.

  • 31.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: Workshop on Emerging Aspects in Information Security2015Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 32.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: SpringerPlus2015Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 33.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: The 30th International Conference on Image and Vision Computing New Zealand ( (IVCNZ 2015)2015Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 34.
    Okoh, Ebenezer
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Biometrics Applications in e-Health Security: A Preliminary Survey2015Ingår i: 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, s. 92-103Konferensbidrag (Refereegranskat)
    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.

  • 35.
    Iqbal, Sarfraz
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Thapa, Devinder
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Päivärinta, Tero
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Conceptual Model of Online Pedagogical Information Security Laboratory: Toward an Ensemble Artifact2015Ingår i: 2015 48th Hawaii International Conference on System Sciences (HICSS 2015): Hawaii, USA, 5-8 January 2015, Piscataway, NJ: IEEE Communications Society, 2015, s. 43-52, artikel-id 7069664Konferensbidrag (Refereegranskat)
    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.

  • 36.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: Computers & Security2014Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 37.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: Intelligent Systems Reference Library, Vol. 702014Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 38.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: Pattern Recognition2014Övrigt (Övrig (populärvetenskap, debatt, mm))
    Abstract [en]

    The Journal of the Pattern Recognition Society

  • 39.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: Science and Information Conference2014Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 40.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: The 29th International Conference on Image and Vision Computing New Zealand (IVCNZ 2014)2014Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 41.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: Workshop on Emerging Aspects in Information Security2014Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 42.
    Hassanien, Aboul Ella
    et al.
    Faculty of Computers and Information, Cairo University.
    Kim, Tai-HoonMultimedia Control and Assurance Laboratory, Hannam University.Kacprzyk, JanuszPolish Academy of Sciences, Systems Research Institute.Awad, Ali IsmailFaculty of Engineering, Al Azhar University, Qena, Egypt.
    Bio-inspiring Cyber Security and Cloud Services: Trends and Innovations2014Samlingsverk (redaktörskap) (Refereegranskat)
  • 43.
    Charif, Bilal
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Business and Government Organizations' Adoption of Cloud Computing2014Ingår i: 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, s. 492-501Konferensbidrag (Refereegranskat)
    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.

  • 44.
    Iqbal, Sarfraz
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Thapa, Devinder
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Design Principles for online Information Security laboratory2014Ingår i: Selected Papers of the Information Systems Research Seminar in Scandinavia, 2014, s. 65-79Konferensbidrag (Refereegranskat)
    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.

  • 45.
    Awad, Ali Ismail
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hassanien, Aboul Ella
    Cairo University.
    Erratum: Impact of Some Biometric Modalities on Forensic Science2014Ingår i: Computational Intelligence in Digital Forensics: Forensic Investigation and Applications, Switzerland: Springer International Publishing , 2014, s. E1-Kapitel i bok, del av antologi (Refereegranskat)
  • 46.
    Awad, Ali Ismail
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Hassanien, Aboul Ella
    Faculty of Computers and Information, Cairo University.
    Impact of Some Biometric Modalities on Forensic Science2014Ingår i: Computational Intelligence in Digital Forensics: Forensic Investigation and Applications, Springer International Publishing , 2014, s. 47-62Kapitel i bok, del av antologi (Refereegranskat)
    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.

  • 47.
    Awad, Ali Ismail
    et al.
    Faculty of Engineering, Faculty of Engineering, Al Azhar University, Qena, Egypt.
    Hassanien, Aboul EllaCairo University.Baba, KensukeKyushu University.
    Advances in Security of Information and Communication Networks: First International Conference, SecNet 2013, Cairo, Egypt, September 3-5, 2013. Proceedings2013Samlingsverk (redaktörskap) (Refereegranskat)
  • 48.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: Communications in Computer and Information Science, Vol. 3812013Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 49.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: Information Sciences2013Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 50.
    Awad, Ali Ismail
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Aktivitet: International Conference on Mobile and Ubiquitous Systems2013Övrigt (Övrig (populärvetenskap, debatt, mm))
12 1 - 50 av 57
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf