Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
A key-management scheme for distributed sensor networks
Proceedings of the 9th ACM conference on Computer and communications security
Random Key Predistribution Schemes for Sensor Networks
SP '03 Proceedings of the 2003 IEEE Symposium on Security and Privacy
Tracking multiple targets with self-organizing distributed ground sensors
Journal of Parallel and Distributed Computing
Disruptive Security Technologies with Mobile Code and Peer-to-Peer Networks
Disruptive Security Technologies with Mobile Code and Peer-to-Peer Networks
Multicast Encryption Infrastructure for Security in Sensor Networks
International Journal of Distributed Sensor Networks
Mobile Network Analysis Using Probabilistic Connectivity Matrices
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
On the Detection of Clones in Sensor Networks Using Random Key Predistribution
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Sensor Network Self-Organization Using Random Graphs
International Journal of Distributed Sensor Networks
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In cloning attacks, an adversary captures a sensor node, reprograms it, makes multiple copies, and inserts these copies, into the network. Cloned nodes subvert sensor network processing from within. In a companion paper [2], we show how to detect and remove clones from sensor networks using random key predistribution security measures. Keys that are present on the cloned nodes are detected by using authentication statistics based on key usage frequency. For consistency with existing random key predistribution literature, and ease of explanation, the network in that paper used an Erdos-Renyi topology. In the Erdos-Renyi topology, the probability of connection between any two nodes in the network is uniform. Since the communications ranges of sensor nodes are limited, this topology is flawed. This article applies the clone detection approach from [2] to more realistic network topologies. Grid and ad hoc topologies reflect the node connectivity patterns of networks of nodes with range limits. We provide analytical methods for choosing detection thresholds that accurately detect clones. We use simulations to verify our method. In particular we find the limitations of this approach, such as the number of nodes that can be inserted without being detected.