On effective data aggregation techniques in Host-based Intrusion Detection in MANET

Abstract

Mobile Ad Hoc Networks (MANETs) have been widely used in commercial and tactical domains. MANETs commonly demand a robust, diverse, energy-efficient, and resilient communication and computing infrastructure, enabling network-centric operation with minimal downtime. MANETs face security risks and energy consumption. However, conducting cyber attack monitoring and detection in a MANET becomes a challenging issue because of limited resources and its infrastructureless network environment. To address this issue, we develop both lossless and lossy aggregation techniques to reduce the energy cost in information transition and bandwidth consumption while preserving the desired detection accuracy. In particular, we develop two lossless aggregation techniques: compression-based and event-based aggregation and develop a lossy aggregation technique: feature-based aggregation. We conduct real-world experiments and simulation study to evaluate the effectiveness of our proposed data aggregation techniques in terms of the energy consumption and detection accuracy.