Volume 10 • Issue 1 • PP: 09–14 • 2026
Trust-Aware Early Detection of Grey-Hole Behaviour in Flying Ad Hoc Wireless Networks: A Data-Driven Study Using Recent FANET Traces
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Flying ad hoc networks (FANETs) enable dynamic multi-hop communication in un-manned aerial nodes, but their routing plane is vulnerable to selective forwarding attacks that decrease packet delivery rates while avoiding the sudden effects of denial. This paper proposes a trust-aware routing and detection approach for early detection of grey-holes in ad hoc flying networks. The paper employs an analysis-ready data set based on the public FAN-GHETS24 data set, a new data set for early time-series classification of attacks in FANETs. The Trust-Aware Routing Grey-Hole Detection (TAR-GHD) model uses a com-bination of link quality evidence, route stability, packet consistency and trust dynamics in a lightweight detection layer that can be executed alongside traditional ad hoc routing. A mathematical formulation is given for evidence aggregation, temporal trust evolution, risk assessment and route warning. The empirical study measures the detection of normal, mild, moderate and heavy grey-hole attacks in various node-density, mobility, observation window, and classification settings. The findings demonstrate that trust and packet-loss dynamics offer reliable early indicators of grey-hole attacks, while mobility and route changes make it harder to distinguish normal loss from malicious loss. The best-performed configuration resulted in an F1-score over 0.93 (held-out evaluation), with the most influential features related to packet delivery, forwarding ratio, trust score and drop-rate dynamics. The results highlight lightweight and explainable trust evidence as a viable technique for enhancing the security of wireless ad hoc routing in UAV-assisted applications.
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References
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