Decision fusion with corrupted reports in multi-sensor networks: A game-theoretic approach

Abstract

Decision fusion in adversarial setting is receiving increasing attention due to its relevance in several applications including sensor networks, cognitive radio, social networks, distributed network monitoring. In most cases, a fusion center has to make a decision based on the reports provided by local agents, e.g. the nodes of a multi-sensor network. In this paper, we consider a setup in which the fusion center makes its decision on the status of an observed system by relying on the decisions made by a pool of local nodes and by taking into account the possibility that some nodes maliciously corrupt their reports to induce a decision error. We do so by casting the problem into a game-theoretic framework and looking for the existence of an equilibrium point defining the optimum strategies for the fusion center and the malicious nodes. We analyze two different strategies for the fusion center: a strategy recently introduced by Varshney et al. in a cognitive radio setup and a new approach based on soft identification of malicious nodes. The superior performance of the new decision scheme are demonstrated by resorting to the game-theoretic framework introduced previously.

A message passing approach for decision fusion in adversarial multi-sensor networks

“…We then use numerical simulations to evaluate the performance of the proposed method for long observation windows. As a result, we show that, even in this case, the proposed solution maintains the performance improvement over the simple majority rule, the hard isolation scheme in [14] and the soft isolation scheme in [16].…”

“…A soft isolation scheme is proposed in [16], where the reports from suspect byzantine nodes are given a lower importance rather being immediately discarded. Even in [16], the lack of knowledge at the FC about the strategy adopted by the attacker (and viceversa) is coped with by adopting a gametheoretic formulation.…”

“…A soft isolation scheme is proposed in [16], where the reports from suspect byzantine nodes are given a lower importance rather being immediately discarded. Even in [16], the lack of knowledge at the FC about the strategy adopted by the attacker (and viceversa) is coped with by adopting a gametheoretic formulation. A rather different approach is adopted in [17], where a tolerant scheme that mitigates the impact of Byzantines on the global decision is used rather that removing the reports submitted by suspect nodes from the fusion procedure.…”

Employing Game Theory and TDMA Protocol to Enhance Security and Manage Power Consumption in WSNs-Based Cognitive Radio

“…Game theory was exploited to formulate the anti-jamming channel selection problem as an anti-jamming dynamic game in CRN [34]. In [35], a zero-sum game was developed to model the corrupted nodes due to the Byzantine attack, which negatively influences the the CRN routing reputation. The harmful impact is caused by the SSDF attack on the FC decision.…”

“…In the literature context, the security in CR can be the essential metric to guarantee the data privacy and to achieve robust communication system, specifically against the intelligent attacks manipulations such as eavesdropper, primary user emulation (PUE), jamming, byzantine, and SSDF attacks [29]. As an eminent adaptive and intelligent tool to address the above security aspects, game theory can be utilized in CRN [30][31][32][33][34][35].The eavesdropper and jamming attacks effect on CRNs, which recognizes the CRN data privacy, were effectively studied using Stackelberg game, zero-sum game, repeated game [30][31][32]. The problem of a full-duplex active eavesdropper, which represents full duplex mode of a jammer and a classical eavesdropper, has been mitigated by a three stage Stackelberg game [30].…”