Location verification in wireless sensor networks (WSNs) is quite challenging in the presence of malicious sensor nodes, which are called attackers. These attackers try to break the verification protocol by reporting their incorrect locations during the verification stage. In the literature of WSNs, most of the existing methods of location verification use a set of trusted verifiers, which are vulnerable to attacks by malicious nodes. These existing methods also use some distance estimation techniques, which are not accurate in noisy channels. In this article, we adopt a statistical approach for secure location verification to overcome these limitations. Our proposed method does not rely on any trusted entities and it takes care of the limited precision in distance estimation by using a suitable probability model for the noise. The resulting verification scheme detects and filters out all malicious nodes from the network with a very high probability even when it is in a noisy channel.
Attaining quantum limited precision of localizing an object in passive imaging
