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Distributed Detection of Node Replication Attacks in Sensor Networks

Bryan Parno, Adrian Perrig, and Virgil Gligor

Abstract

The low-cost, off-the-shelf hardware components in unshielded sensor-network nodes leave them vulnerable to compromise. With little effort, an adversary may capture nodes, analyze and replicate them, and surreptitiously insert these replicas at strategic locations within the network. Such attacks may have severe consequences; they may allow the adversary to corrupt network data or even disconnect significant parts of the network. Previous node replication detection schemes depend primarily on centralized mechanisms with single points of failure, or on neighborhood voting protocols that fail to detect distributed replications. To address these fundamental limitations, we propose two new algorithms based on emergent properties, i.e., properties that arise only through the collective action of multiple nodes. Randomized Multicast distributes node location information to randomly-selectedwitnesses, exploiting the birthday paradox to detect replicated nodes, while Line-Selected Multicast uses the topology of the network to detect replication. Both algorithms provide globally-aware, distributed node-replica detection, and Line-SelectedMulticast displays particularly strong performance characteristics. We show that emergent algorithms represent a promising new approach to sensor network security; moreover, our results naturally extend to other classes of networks in which nodes can be captured, replicated and re-inserted by an adversary.

Details

Publication typeInproceedings
Published inProceedings of the 2005 IEEE Symposium on Security and Privacy
PublisherIEEE
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