Study of wormhole attack detecting based on local connectivity information in wireless sensor networks

Wormhole attack is a severe security threat to wireless sensor networks, and it is commonly considered challenging to detect and prevent because of its independence of MAC protocols and immunity to cryptology techniques. Nearly all the existing defenses have impractical requirements on the network, such as directional antenna, specialized GPS unit, or even tight time synchronization, which means previous approaches may not have perfect applicability in practice. In this paper, we present our primary research for the effect of wormhole attack on network topology, or local connectivity information, and develop both centralized and distributed algorithms for detecting wormhole attack in wireless sensor networks. The approaches proposed in this work not only require neither global topology information nor specialized hardware, but also can minimize wormhole related security risk by discriminating normal neighbors from illusive ones and removing the latter from neighbor lists. As only abnormal nodes get involved in detection procedures, compared with other approaches, sensor nodes in our schemes consume much less energy and algorithm complexity get further reduced. We present simulation results for models with different parameters, and show that the algorithms are able to detect wormhole attacks with a 100% detection and 0% false alarm probabilities using proper parameters.