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CREST lets VANET vehicles abstain on weak event evidence

Original title: From Trust Scores to Driver Decisions: An Abstaining Evidential Decision Layer for Event Validation in VANETs

arXiv cs.CRby İpek Abasıkeleş Turgut ()1 min read1 · 1 read
AI summary · x-ai/grok-4.7Summaries by Vani AI

In a simulation of fourteen attacks, CREST cut two trust systems' decision error from 0.162 and 0.106 to 0.051.

The paper presents CREST, a vehicle-side framework for deciding whether a reported VANET event is real. Vehicles weight reports by sender trust, proximity and freshness, fuse them with Yager's rule, and abstain until the fused margin meets a threshold. Unresolved cases follow an explicit application policy. A pre-registered simulation with fourteen attacks, including position spoofing and trust-gated camouflage, reports lower decision error than two published trust-based dissemination systems.

Unconfirmed: Results come from the authors' pre-registered simulation, not a deployed VANET.

Key facts
  • A single report can change the decision margin by at most its weight.
  • Attacker-coalition influence is bounded by the coalition's trust.
  • The best-guess policy lowered both missed hazards and unnecessary reroutes.
  • CREST beat the forced binary rule on both error types in every cell.
  • All unspecified parameters were tuned by the same procedure.
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From the original article

1 min read at arxiv.org

Trust management in vehicular ad hoc networks is highly active, yet the decision that a driver needs, whether a reported event is real, has received far less attention; the schemes that make it force every decision into two outcomes, even on thin or conflicting evidence. This paper presents CREST, a vehicle-side event-decision framework that can withhold a decision its evidence does not support.

arXiv cs.CR

By İpek Abasıkeleş Turgut · arxiv.org

Read the full article at arXiv cs.CR

A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.