On effective data aggregation techniques in host-based intrusion detection in MANET

Abstract

A Mobile Ad Hoc Network (MANET) has been used in both commercial and tactical applications and faces security risks. Conducting cyber–attack monitoring and detection in MANET is challenging owning to limited resources. To deal with this issue, in this paper we develop lossless and lossy aggregation techniques to reduce the resources (e.g., energy consumption and bandwidth use) for transmitting security information through MANET while preserving the desired detection accuracy for cyber security operation. Particularly, our novel compression–based data aggregation technique effectively removes the duplicated information and compresses the pivotal data. The event–based data aggregation consolidates the data with the same type of predefined events. We also develop lossy data aggregation technique, namely feature–based data aggregation, which defines a series of basic features. We conduct real–world experiments and simulations to evaluate the effectiveness of our proposed data aggregation techniques in terms of energy consumption and detection accuracy.