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A Novel Approach for Network Attack Classification Based on Sequential Questions Md Mehedi Hassan Onik, Nasr Al-Zaben, Hung Phan Hoo and Chul-Soo Kim Abstract: With the development of incipient technologies, user devices becoming more exposed and ill-used by foes. In upcoming decades, traditional security measures will not be sufficient enough to handle this huge threat towards distributed hardware and software. Lack of standard network attack taxonomy has become an indispensable dispute on developing a clear understanding about the attacks in order to have an operative protection mechanism. Present attack categorization techniques protect a specific group of threat which has either messed the entire taxonomy structure or ambiguous when one network attacks get blended with few others attacks. Hence, this raises concerns about developing a common and general purpose taxonomy. In this study, a sequential question-answer based model of categorization is proposed. In this article, an intrusion detection framework and threat grouping schema are proposed on the basis of four sequential questions (“Who”, “Where”, “How” and “What”). We have used our method for classifying traditional network attacks in order to identify initiator, source, attack style and seriousness of an attack. Another focus of the paper is to provide a preventive list of actions for network administrator as a guideline to reduce overall attack consequence. Recommended taxonomy is designed to detect common attacks rather than any particular type of attack which can have a practical effect in real life attack classification. From the analysis of the classifications obtained from few infamous attacks, it is obvious that the proposed system holds certain benefits related to the prevailing taxonomies. Future research directions have also been well acknowledged. Keywords: Network attack taxonomy; Intrusion detection; Network vulnerabilities; Sequential question; Virus attack security; Virus attack classification; Attack taxonomies; Attack Surfaces. |
Stereoscopic Human Detection in a Natural Environment Ross Davies, Ian Wilson and Andrew Ware Abstract: The algorithm presented in this paper is designed to detect people in real-time from 3D footage for use in Augmented Reality applications. Techniques are discussed that hold potential for a detection system when combined with stereoscopic video capture using the extra depth included in the footage. This information allows for the production of a robust and reliable system. To utilise stereoscopic imagery, two separate images are analysed, combined and the human region detected and extracted. The greatest benefit of this system is the second image, which contains additional information to which conventional systems do not have access, such as the depth perception in the overlapping field of view from the cameras. We describe the motivation behind using 3D footage and the technical complexity of human detection. The system is analysed for both indoor and outdoor usage, when detecting human regions. The developed system has further uses in the field of motion capture, computer gaming and augmented reality. Novelty comes from the camera not being fixed to a single point. Instead, the camera is subject to six degrees of freedom (DOF). In addition, the algorithm is designed to be used as a first filter to extract feature points in input video frames faster than real-time. Keywords: 3D Image; Human Detection; Human Tracking; Foreground Detection. |
Intra-building People Localisation Using Personal Bluetooth Low Energy (BLE) Devices Glebs Kuzmics and Maaruf Ali Abstract: This paper discusses the conceptual implementation of a system to locate people inside buildings using their personal Bluetooth® low energy device(s) in situations of a crisis. Various aspects of BLE technology are covered with regard to their usage for emergency management. Legal, social, ethical and professional issues are also discussed in using this technology, especially in matters of safeguarding information privacy. The plan of the proposed system is then discussed and concluded. Keywords: Localization; Bluetooth Low Energy; BLE; Location Based Services; LBS; Crisis Intervention. |
Mobile Assisted Language Learning (MALL) – A Brief Survey Maaruf Ali and Shayma K. Miraz Abstract: This research article presents a brief survey of language learning applications implemented on mobile computing devices, such as cellular mobile phones. The corpus of the literature show the efficacy and effectiveness of using mobile devices to disseminate, train, retain and improve the linguistic ability of non-native speakers. Keywords: Mobile Assisted Language Learning; MALL; Mobile Learning; e-learning. |
Cross-cultural Usability Issues in E/M-Learning Mahdi H. Miraz, Maaruf Ali and Peter S. Excell Abstract: This paper gives an overview of electronic learning (E-Learning) and mobile learning (M-Learning) adoption and diffusion trends, as well as their particular traits, characteristics and issues, especially in terms of cross-cultural and universal usability. E-Learning and M-Learning models using web services and cloud computing, as well as associated security concerns are all addressed. The benefits and enhancements that accrue from using mobile and other internet devices for the purposes of learning in academia are discussed. The differences between traditional classroom-based learning, distance learning, E-Learning and M-Learning models are compared and some conclusions are drawn. Keywords: Cross-cultural Usability; E-Learning (Electronic Learning); M-Learning (Mobile Learning); Virtual Learning Environments (VLE); Virtual Education; Online Education; Technology-enhanced Learning (TEL); Blended Learning. |
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