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Ad hoc networks are natively cooperative systems in the sense that their nodes have to relay data to one another. The inherent drawback of this scheme is that it renders these networks susceptible to intruders. Collaborative attacks, in which various attackers may coordinate actions to hit the network stronger, are also facilitated by the natural cooperation existing in ad networks. In this paper, the authors discuss the most important forms of attacks, address possible collaborations among attackers, show how machine learning techniques and signal processing techniques can be used to detect and defend against collaborative attacks in such environments, and discuss implementation issues. They also perform evaluations to determine the best design options for their preliminary proposed scheme to collaboratively respond to attacks.
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