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IPEK: Intelligent Priority-Aware Event-Based Trust with Asymmetric Knowledge for Resilient Vehicular Ad-Hoc Networks

arXiv Security Archived Apr 10, 2026 ✓ Full text saved

arXiv:2604.07532v1 Announce Type: cross Abstract: Vehicular Ad Hoc Networks (VANETs) are vulnerable to intelligent attackers who exploit the homogeneous treatment of traffic events in existing trust models. These attackers accumulate reputation by reporting correctly on low-priority events and then inject false data during safety-critical situations - a strategy that current approaches cannot detect because they ignore event severity and location criticality in trust calculations. This paper add

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    Computer Science > Networking and Internet Architecture [Submitted on 8 Apr 2026] IPEK: Intelligent Priority-Aware Event-Based Trust with Asymmetric Knowledge for Resilient Vehicular Ad-Hoc Networks İpek Abasıkeleş Turgut Vehicular Ad Hoc Networks (VANETs) are vulnerable to intelligent attackers who exploit the homogeneous treatment of traffic events in existing trust models. These attackers accumulate reputation by reporting correctly on low-priority events and then inject false data during safety-critical situations - a strategy that current approaches cannot detect because they ignore event severity and location criticality in trust calculations. This paper addresses this gap through three contributions. First, it introduces event-aware and location-aware intelligent attack models, which have not been formally defined or simulated in prior work. Second, it proposes an asymmetric local trust mechanism where penalties scale with event and location severity while rewards follow an asymptotic model, making trust difficult to regain after misuse. Third, it adapts Dempster-Shafer Theory for global trust fusion using Yager's combination rule - assigning conflicting evidence to uncertainty rather than forcing premature decisions - combined with sequential source-reliability ordering and an asymmetric risk accentuation mechanism. Simulations using OMNeT++, Veins, and SUMO compare the proposed system (IPEK) against MDT and TCEMD under attacker densities of 15-35 percent. IPEK maintained 0 percent False Positive Rate across all scenarios, meaning no honest vehicle was wrongly revoked, while sustaining Recall above 75 percent and F1-scores exceeding 0.86. These results demonstrate that integrating context-awareness into both attack modeling and trust evaluation significantly outperforms symmetric approaches against strategic adversaries. Subjects: Networking and Internet Architecture (cs.NI); Cryptography and Security (cs.CR) Cite as: arXiv:2604.07532 [cs.NI]   (or arXiv:2604.07532v1 [cs.NI] for this version)   https://doi.org/10.48550/arXiv.2604.07532 Focus to learn more Submission history From: İpek AbasıkeleşTurgut [view email] [v1] Wed, 8 Apr 2026 19:15:28 UTC (3,504 KB) Access Paper: HTML (experimental) view license Current browse context: cs.NI < prev   |   next > new | recent | 2026-04 Change to browse by: cs cs.CR References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Apr 10, 2026
    Archived
    Apr 10, 2026
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