Harnessing Node Multiplicity for Detecting and Mitigating False Data in Wireless Relay Networks

Abstract

We present the physical-layer maximum a posteriori (MAP) test for detecting false data in multiple-source wireless relay networks. The MAP test, which minimizes the average probability of detection error, exploits the noisy (erroneous) information about the true packet that the destination receives (overhears) directly from the source nodes as a reference. We show that the average probability of detection error decreases exponentially as the number of source nodes increases, regardless of the reliability of the reference information. This indicates that the multiplicity of source nodes can be leveraged to construct a powerful integrity check mechanism for detecting false data at the destination. We also present a parallel MAP test that improves the detection accuracy when the number of source nodes is limited and overhearing channel disparities are high. Then, we present a packet recovery mechanism to recover false alarmed packets, i.e. unmodified packets that are mistakenly declared as modified, by the MAP test and thereby to improve the throughput.