Energy-aware node reliability and route obfuscation mechanism for traffic analysis attack detection in scalable RPL-based IoT–LLNs

Abstract In the digital era, the IPv6 routing protocol for low-power and lossy networks (RPL) has found a prevalent application in the Internet of Things–low power and lossy networks (IoT–LLN) environment. However, the RPLs are deeply vulnerable to Blackhole and traffic analysis attacks. Blackhole attacks may drop all received packets instead of forwarding them to relay nodes, whereas the traffic analysis attacks introduce the network traffic intentionally. These attacks pose serious threats to the confidentiality, energy efficiency, and reliability of the IoT–LLNs environment. Therefore, this work presents a novel energy-aware node reliability and trusted route detection (NRTRD) framework to alleviate the various routing and security problems. Primarily, the proposed NRTRD framework executes the fuzzy logic-based reliable node identification method to detect black hole attacks. The priority-enabled trusted route mechanism is then invoked in the proposed framework to control the network traffic that provides a secure route between the nodes. Three different performance evaluations with respect to scalability, attack diagnosis, and Quality of Service (QoS) can be carried out to test the suggested systems. The scalability analysis has been accomplished by varying the sink location, simulation area, node density, and attack probability rates. The results demonstrate that the proposed NRTRD achieves an enhanced accuracy of 96.44% when compared to existing techniques.