A Secure Optimum Distributed Detection Scheme in Under-Attack Wireless Sensor Networks

We address the problem of centralized detection of a binary event in the presence of
$\beta$
fraction falsifiable sensor nodes (SNs) (i.e., controlled by an attacker) for a bandwidth-constrained
under-attack
spatially uncorrelated distributed wireless sensor network. The SNs send their 1-bit test statistics over orthogonal channels to the fusion center (FC), which linearly combines them to reach to a final decision. Adopting the modified deflection coefficient as an alternative function to be optimized, we first derive in a closed-form the FC optimal weights combining. But as these optimal weights require
a priori
knowledge that cannot be attained in practice, this optimal weighted linear FC rule is not implementable. We also derive in a closed-form the expressions for the attacker “flipping probability” (defined in paper) and the minimum fraction of compromised SNs that makes the FC incapable of detecting. Next, based on the insights gained from these expressions, we propose a novel and noncomplex reliability-based strategy to identify the compromised SNs, and then, adapt the weights combining proportional to their assigned reliability metric. In this way, the FC identifies the compromised SNs and decreases their weights in order to reduce their contributions towards its final decision. Finally, simulation results illustrate that the proposed strategy significantly outperforms (in terms of FC's detection capability) the existing compromised SNs identification and mitigation schemes.