In this paper we investigate the behavior of degree-based clustering algorithms with respect to their stability and attack-resistance. Our attack scenario tries to bias the clustering head selection procedure by sending faulty degree claims. We propose a randomized variant of the highest degree algorithm which is proved, through experimental results, attack-resistant without imposing significant overhead to the clustering performance. In addition, we extend our proposal with a cooperative consistent clustering algorithm which integrates security into the clustering decision achieving attacker identification and classification.
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Tselikis et al. (2012) studied this question.
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