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Energy-aware and self-adaptive anomaly detection scheme based on network tomography in mobile ad hoc networks

Authors :
Wang, Wei
Wang, Huiran
Wang, Beizhan
Wang, Yaping
Wang, Jiajun
Source :
Information Sciences. Jan2013, Vol. 220, p580-602. 23p.
Publication Year :
2013

Abstract

Abstract: Anomaly detection is indispensable for satisfying security services in mobile ad hoc network (MANET) applications. Often, however, a highly secure mechanism consumes a large amount of network resources, resulting in network performance degradation. To shift intrusion detection from existing security-centric design approaches to network performance centric design schemes, this paper presents a framework for designing an energy-aware and self-adaptive anomaly detection scheme for resource constrained MANETs. The scheme uses network tomography, a new technique for studying internal link performance based solely on end-to-end measurements. With the support of a module comprising a novel spatial-time model to identify the MANET topology, an energy-aware algorithm to sponsor system service, a method based on the expectation maximum to infer delay distribution, and a Self-organizing Map (SOM) neural network solution to profile link activity, the proposed system is capable of detecting link anomalies and localizing malicious nodes. Consequently, the proposed scheme offers a trade-off between overall network security and network performance, without causing any heavy network overload. Moreover, it provides an additional approach to monitor the spatial-time behavior of MANETs, including network topology, link performance and network security. The effectiveness of the proposed schemes is verified through extensive experiments. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
00200255
Volume :
220
Database :
Academic Search Index
Journal :
Information Sciences
Publication Type :
Periodical
Accession number :
83189900
Full Text :
https://doi.org/10.1016/j.ins.2012.07.036