SecMCL: A Secure Monte Carlo Localization algorithm for mobile sensor networks

Recently with the emergence of mobile sensor networks, localization for such networks has gained much attention, and many localization algorithms have been proposed. Among them the sequential Monte Carlo (SMC) based algorithms are very popular because of their simplicity and efficiency. However, most current SMC-based localization algorithms implicitly assume there is no attacker in the network, which may not be true in real applications. The attackers, if any, may send false information by themselves or through compromised nodes to disturb the localization. In this paper, we present the design and evaluation of a secure Monte Carlo localization algorithm, SecMCL. SecMCL provides authentication to messages and employs a new sampling method to defeat attacks. Simulation results show that SecMCL greatly improves the localization accuracy of existing SMC-based localization method when there are attacks. Also, compared with existing SMC localization method, SecMCL incurs no communication cost (in terms of number of messages) and achieves the same localization accuracy when there is no attack.