A multi-layer data fusion system for Wi-Fi attack detection using automatic belief assignment

Wireless networks are increasingly becoming susceptible to more sophisticated threats. An attacker may spoof the identity of legitimate users before implementing more serious attacks. Most of the current Intrusion Detection Systems (IDS) that employ multi-layer approach to help towards mitigating network attacks, offer high detection accuracy rate and low numbers of false alarms. Dempster-Shafer theory has been used with the purpose of combining beliefs of different metric measurements across multiple layers. However, an important step to be investigated remains open; this is to find an automatic and self-adaptive process of Basic Probability Assignment (BPA). This paper describes a novel BPA methodology able to automatically adapt its detection capabilities to the current measured characteristics, with a light weight process of generating a baseline profile of normal utilisation and without intervention from the IDS administrator. We have developed a multi-layer based application able to classify individual network frames as normal or malicious

An automatic and self-adaptive multi-layer data fusion system for WiFi attack detection

Wireless networks are becoming susceptible to increasingly more sophisticated threats. Most of the current intrusion detection systems (IDSs) that employ multi-layer techniques for mitigating network attacks offer better performance than IDSs that employ single layer approach. However, few of the current multi-layer IDSs could be used off-the-shelf without prior thorough training with completely clean datasets or a fine tuning period. Dempster-Shafer theory has been used with the purpose of combining beliefs of different metric measurements across multiple layers. However, an important step to be investigated remains open; this is to find an automatic and self-adaptive process of basic probability assignment (BPA). This paper describes a novel BPA methodology able to automatically adapt its detection capabilities to the current measured characteristics, without intervention from the IDS administrator. We have developed a multi-layer-based application able to classify individual network frames as normal or malicious with perfect detection accuracy. Copyright © 2013 Inderscience Enterprises Ltd

Protocols for Wireless Sensor Networks: A Survey, Journal of Telecommunications and Information Technology, 2018, nr 1

This paper presents a survey on the MAC and network layer of Wireless Sensor Networks. Performance requirements of the MAC layer are explored. MAC layer protocols for battery-powered networks and energy harvesting-based networks are discussed and compared. A detailed discussion on design constraints and classification of routing protocols is presented. Several routing protocols are compared in terms of such parameters as: energy consumption, scalability, network lifetime and mobility. Problems that require future research are presented. The cross-layer approach for WSNs is also surveyed

Journal of Telecommunications and Information Technology, 2018, nr 1

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