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IPEK: Event-Criticality-Aware Evidential Trust Management against Strategic Insider Attacks in Vehicular Ad Hoc Networks
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arXiv:2604.07532v3 Announce Type: replace-cross Abstract: Event-based trust management in vehicular ad hoc networks is vulnerable to strategic insider attackers who report trivial events correctly to build reputation, falsify reports on safety-critical events, and corrupt the trust feedback they provide about other vehicles. This paper proposes IPEK, an event-criticality-aware evidential trust management framework. IPEK combines an asymmetric local trust that scales rewards and penalties with event severity and location criticality, a reporter-credibility test that discounts feedback deviating systematically from the consensus of witnesses, and a Dempster-Shafer global trust that fuses feedback with Yager's rule, historical combination and risk accentuation. Closed-form properties quantify how quickly trust is lost and regained and show why Yager's rule keeps the global state revisable. IPEK is evaluated in simulation against a trust cascading-based dissemination scheme and the beta reputation system under eight attacks, with severity-, location-, on-off- and continuously triggered attackers falsifying their reports alone or also their feedback, at attacker ratios from 10% to 40%. Threshold-free separation measures are complemented by closed-loop revocation with frozen thresholds. With up to 25% attackers, IPEK achieves a significantly higher F1-score than both baselines under all attacks, with false positive rates of 0.9-15.5% against 7.8-49.7% and 26.0-41.4%, and it remains robust up to 40% attackers when only reports are falsified. Under fully colluding attackers that also corrupt feedback, all methods break down beyond about one third of attackers; this envelope and a longer detection delay are reported as limitations.
Source:https://arxiv.org/abs/2604.07532PreviousDIALER: A Case for Improving Rare-Class Accuracy in Retraining-Free Edge Video AnalyticsNextS4oP: Operator-level Pruning of Structured State Space Models for Resource-Constrained Devices
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