Comprehensive Analysis of Blackhole Attack on RPL in Static, Mobile and Hybrid Network Environment

The Routing Protocol for Low-Power and Lossy Networks (RPL), extensively applied in IoT applications, is susceptible to the Blackhole attack, wherein hostile nodes discard packets without transmission, resulting in considerable loss of network performance. This attack jeopardizes the reliability and usefulness of RPL-based networks, particularly in crucial applications like environmental monitoring and healthcare. Understanding the effects of Blackhole attacks in diverse network environments—static, mobile, and hybrid—is vital for creating personalized security solutions. Every scenario provides various issues, including the stability of static networks and the dynamic nature of mobile and hybrid setups, which determine the severity of the attack. This study performs a comparative investigation of the impact of Blackhole attacks on RPL-based networks in static, mobile, and hybrid scenarios. Simulations were done with varied node densities (10, 20, and 30 nodes) and different percentages of malicious nodes (10%, 20%, and 30%). Key performance indicators, such as Packet Delivery Ratio (PDR), Average End-to-End Delay (AE2ED), overhead packets, energy utilization, and throughput, were investigated across these conditions. The analysis suggests that static networks, however more robust to random attacks, are susceptible to disruption when Blackhole nodes interfere with important links. Mobile networks incur the highest performance deterioration due to frequent route changes and increasing energy demand. Hybrid networks, having both static and mobile nodes, demonstrate intermediate susceptibility but are more affected by mobile attackers. Overall, the statistics imply that mobility improves the impact of Blackhole attacks. The findings underscore the need for environment-specific security solutions in RPL-based networks. Static networks demand stronger detection systems for targeted attacks, while mobile and hybrid environments need adaptable, low-overhead security solutions that can handle changing topologies. These insights will inspire future attempts to increase the security and dependability of IoT networks under Blackhole attacks.