REVS-T: Trust-Tier-Aware Provider Selection for Secure Vehicular Computation Offloading

Abstract

Vehicular computation offloading (VCOff) enables resource-constrained vehicles to delegate delay-sensitive tasks to nearby providers. However, it remains vulnerable to strategic malicious nodes that withhold results, or behave intermittently to evade detection. Although reputation values evolve across repeated interactions, long-term security depends on how these signals are governed and enforced at the decision layer. This paper introduces REVS-T, a four-tier governance and tieraware selection mechanism using reputation bands, warningstreak escalation, and pool partitioning. Under persistent attack at 50% adversarial ratio, REVS-T achieves 91.9% task success and 96.7% malicious avoidance with zero false exclusions, outperforming Threshold by 5.5% and Beta by 14.9%. A four-step ablation under shared reputation-update logic shows composite scoring and four-tier governance as the dominant drivers, with ST-conditioned initialization providing phase-shift adaptation and a fairness guarantee no evaluated baseline achieves.