<scp>TRUST</scp> ‐Loc: A Unified Framework for Trust‐Based Localization in <scp>IoT</scp> Under Sybil and Beacon Spoofing Attacks

ABSTRACT The Internet of Things (IoT) relies on trust and localization to transmit data securely and efficiently. However, IoT networks remain vulnerable to identity‐based attacks like Sybil and Beacon spoofing attacks, which disrupt the routing, compromise sensor node localization, and degrade network performance. Existing Trust‐based and RPL‐enhanced mechanisms often struggle to detect advanced Sybil behaviors and beacon manipulation, particularly in dynamic IoT environments. Many approaches rely on static trust models or introduce significant overhead, creating a clear need for a lightweight yet accurate detection framework. In this paper, we have introduced the trust‐based localization called TRUST‐Loc, which deals with Sybil attack Type‐I (fake parent), Type‐II (sequence mismatch), Type‐III (dynamic identity manipulation), and Beacon spoofing attack. An integration of Highest Common Rank (HCR) and Lowest Cost Rank (LCR) is used, which verifies the consistency in child–parent relationship and applies the Receive signal strength indicator (RSSI) &amp; Time Correlation mechanism that frames a Beacon spoofing attack. A lightweight, adaptive heuristic model enables resource‐efficient operation for Trust score computation. The proposed TRUST‐Loc is simulated in the Cooja simulator, and simulation results demonstrate that TRUST‐Loc significantly improves the True positive detection (up to 99.95%), maintains a high packet delivery ratio, and reduces energy and memory overhead compared to the standard Routing Protocol for Low‐Power and Lossy Networks (RPL). Experimental results show that our proposed TRUST‐Loc is a promising lightweight solution.