A context-aware information-based clone node attack detection scheme in Internet of Things

The rapidly expanding nature of the Internet Things (IoT) networks is beginning to attract interest across a range applications, including smart homes, transportation, health, and industrial contexts such as robotics. This cutting-edge technology enables individuals track control their integrated environment in real-time remotely via thousands IoT devices comprised sensors actuators that actively participate sensing, processing, storing sharing information. Nonetheless, are frequently deployed hostile environments, wherein adversaries attempt capture them order seize entire network. One example potentially malicious behaviour cloning devices, which an attacker can physically obtain some sensitive information, duplicate intelligently deploy desired locations conduct various insider attacks. A device attack on significant security concern since it allows for selective forwarding, sink-hole, black-hole, warm-hole To address this issue, paper provides efficient scheme detecting clone node mobile uses semantic information known context locate securely. We design location proof mechanism by combining proofs batch verification extended elliptic curve digital signature technique (ECDSA*) accelerate process at selected trusted nodes. Furthermore, we present model selecting trustworthy based profile capabilities, enabling be chosen from other proof-verification procedure. Compared with existing studies, performance analysis experimental results suggest our proposed high degree detection accuracy minimal time significantly reduces computation, communication, energy storage overheads.