Privacy-Preserving And Real-time Detection Of Clone Attacks In Wireless Sensor Networks

Clone attack is a serious security threat for WSN(wireless sensor network). Clone attack is dangerous because they allow the attacker to control over much of the network with a few clones. Researchers have carried out a lot of related work against clone attacks. Most of current schemes can prevent clone attacks, efficient or not, however only in certain circumstance. Traditional solution is mainly divided into two kinds, centralized and distributed. The centralized methods need a base station to detect the clone nodes. This may lead to single-point failure and fast energy depletion of the sensor nodes around the base station. The distributed methods can solve the single-point failure, however may suffer from high communication cost and poor detection accuracy. Most of all, both of these schemes need security information(ID, keys, codes, etc.), this may lead to privacy disclosure. The privacy disclosure is very dangerous as the attackers can rebuild the topology of the sensor network and thread the whole area with collecting the privacy information.In order to solve the privacy issues and clone attack problems in WSN, we study the privacy content extraction and clone attack detection. Firstly, we need to solve the privacy content extraction, as this problem is the foundation of clone attack detection. It is because of the ignore of privacy content extraction, there comes the flood of the privacy disclosure. With the foundation of association network, we build the model of privacy information of users. Then we study the privacy information extraction in physical network and logical network and build the topology of logical network with the property of logical network. Through the study of privacy extraction for physical network and logical network, we utilize the superimposed s-disjunct code to compute the social fingerprint. We also utilize an additively homomorphic encryption to generate the fingerprint which is a brilliant solution for preventing privacy disclosure. Based on the privacy content extraction, we proposed our clone attack detection method. Our method can work on both centralized and distributed way. Our method can also solve the single point failure and high communication cost. Finally, we give the correctness analysis of our scheme and verify the effectiveness by experiment.