WormPlanar: Topological Planarization Based Wormhole Detection in Wireless Networks

Wormhole attack is a severe threat to wireless ad hoc and sensor networks. Most of previous countermeasures either require specialized hardware devices or make strong assumptions on the network in order to capture the specific symptom induced by wormholes. Those requirements and assumptions limit the applicability of those approaches. Recently, some approaches based on topological or graph theoretical techniques are proposed to recognize wormholes using only connectivity information, shedding light on the challenging issue of connectivity-based wormhole detections. Unfortunately, those state-of-the-art connectivity-based countermeasures either present the principle of tracing wormholes in continuous domain, which makes it costly to transform them into protocols in discrete networks, or only explore localized (unstable) symptom of wormholes, accordingly incurring high false positive or negative rate. In this work, we make the first attempt towards establishing a graph theoretical method, called Worm Planar, that merely utilizes localized connectivity information and is able to capture the global essential symptoms of wormholes directly in the discrete networks. Worm Planar exploits location free network planarization technique to perform connectivity-based wormhole detection. Our new insights into the symptoms of wormholes make Worm Planar orthogonal to existing connectivity-based methods. We formally prove the correctness and evaluate the effectiveness of our approach through extensive simulations and comparisons with the state-of-the-art approaches. Simulation results demonstrate that Worm Planar is able to accurately identify and isolate wormholes for a large class of network instances.