Mobile ad hoc networks (MANETs) have experienced rapid growth in their use for various military, medical, and commercial scenarios. This is due to their dynamic nature that enables the deployment of such networks, in any target environment, without the need for a pre-existing infrastructure. On the other hand, the unique characteristics of MANETs, such as the lack of central networking points, limited wireless range, and constrained resources, have made the quest for securing such networks a challenging task. A large number of studies have focused on intrusion detection systems (IDSs) as a solid line of defense against various attacks targeting the vulnerable nature of MANETs. Since cooperation between nodes is mandatory to detect complex attacks in real time, various solutions have been proposed to provide cooperative IDSs (CIDSs) in efforts to improve detection efficiency. However, all of these solutions suffer from high rates of false alarms, and they violate the constrained-bandwidth nature of MANETs. To overcome these two problems, this research presented a novel CIDS utilizing the concept of social communities and the Dempster-Shafer theory (DST) of evidence. The concept of social communities was intended to establish reliable cooperative detection reporting while consuming minimal bandwidth. On the other hand, DST targeted decreasing false accusations through honoring partial/lack of evidence obtained solely from reliable sources. Experimental evaluation of the proposed CIDS resulted in consistently high detection rates, low false alarms rates, and low bandwidth consumption. The results of this research demonstrated the viability of applying the social communities concept combined with DST in achieving high detection accuracy and minimized bandwidth consumption throughout the detection process.
|Commitee:||Gowing, Glyn, Peixiang, Liu|
|School:||Nova Southeastern University|
|School Location:||United States -- Florida|
|Source:||DAI-B 80/06(E), Dissertation Abstracts International|
|Keywords:||Cooperative, Cybersecurity, Intrusion detection, Manet, Networking|
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