Mitigation and Performance Analysis of Internal Routing Attacks in RPL-Based IoT Networks under Different Node Deployments

The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is the de facto standard for multi-hop communication in the Internet of Things (IoT). Despite extensive research on individual attack types, the combined influence of node-placement geometry and routing attacks on RPL resilience remains poorly quantified. This paper presents a comprehensive, topology-aware vulnerability model built through thirty independent Contiki 2.7 (Cooja 1.2) simulations for each of four internal attacks—flooding, selective forwarding, DIO suppression, and replay—across three representative geometries: random, linear, and elliptical. Each scenario employed twenty legitimate Sky motes and five malicious nodes for ten-minute runs, producing a statistically validated dataset of delivery , loss, and energy metrics. Results reveal a decisive geometric effect: while random layouts sustain ≈ 97 % Packet Delivery Ratio (PDR) with moderate Energy per Correctly delivered Packet (ECPP 0.1 J), elliptical networks collapse under replay with PDR < 2 % and ECPP > 4.9 J. Two-way ANOVA and post-hoc tests confirm topology as a dominant factor (p < 0.001, η 2 = 0.78). Finally, a lightweight topology-aware hardening mechanism is proposed, integrating adaptive Trickle timers, duplicate-sequence monitors, and energy-biased parent selection. The findings establish topology geometry as a first-order design variable for secure, energy-efficient RPL deployment in next-generation IoT and industrial networks.