Arboricity and bipartite subgraph listing algorithms
Information Processing Letters
Secure verification of location claims
WiSe '03 Proceedings of the 2nd ACM workshop on Wireless security
The sybil attack in sensor networks: analysis & defenses
Proceedings of the 3rd international symposium on Information processing in sensor networks
SECTOR: secure tracking of node encounters in multi-hop wireless networks
Proceedings of the 1st ACM workshop on Security of ad hoc and sensor networks
Visualization of wormholes in sensor networks
Proceedings of the 3rd ACM workshop on Wireless security
LITEWORP: A Lightweight Countermeasure for the Wormhole Attack in Multihop Wireless Networks
DSN '05 Proceedings of the 2005 International Conference on Dependable Systems and Networks
Boundary recognition in sensor networks by topological methods
Proceedings of the 12th annual international conference on Mobile computing and networking
Journal of Network and Computer Applications - Special issue: Network and information security: A computational intelligence approach
TrueLink: A Practical Countermeasure to the Wormhole Attack in Wireless Networks
ICNP '06 Proceedings of the Proceedings of the 2006 IEEE International Conference on Network Protocols
WormCircle: Connectivity-Based Wormhole Detection in Wireless Ad Hoc and Sensor Networks
ICPADS '09 Proceedings of the 2009 15th International Conference on Parallel and Distributed Systems
Statistical wormhole detection in sensor networks
ESAS'05 Proceedings of the Second European conference on Security and Privacy in Ad-Hoc and Sensor Networks
IEEE Transactions on Signal Processing
Wormhole attacks in wireless networks
IEEE Journal on Selected Areas in Communications
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A wormhole attack places two radio transceivers connected by a high capacity link and retransmits wireless signals from one antenna at the other. This creates a set of shortcut paths in the network, and may attract a lot of traffic to the wormhole link. The link thus gains control of a large fraction of network traffic which opens the door for more dangerous attacks afterwards. In this paper we introduce a wormhole detection and removal algorithm based on local connectivity tests. The basic idea is that the neighborhood of a wormhole contains two sets of nodes corresponding to two sides of the wormhole. The distance between these two sets is small when using paths that pass through the wormhole link, but is large when only regular network paths are considered. Thus we remove a small neighborhood that will contain potential wormhole links and check if a slightly larger neighborhood falls apart to multiple connected components. To accommodate spatial and temporal unpredictability of wireless communication links we abstract the network connectivity as an arbitrary graph so that the method does not assume any idealistic models (such as unit disk graph model). The algorithm uses purely local connectivity information, handles multiple wormhole attacks and generalizes to wireless networks deployed in 3D. It does not suffer from typical limitations in previous work such as the requirements of special hardware, communication models, synchronization, node density etc. In simulations, our method is seen to beat the state of the art solutions, in particular for cases where previous solutions experience poor performance.