Print Email Facebook Twitter Detection and mitigation technique against collusion attack in RPL-Based IoT networks Title Detection and mitigation technique against collusion attack in RPL-Based IoT networks Author Essaadi, David (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Intelligent Systems) Contributor Lal, C. (mentor) Conti, M. (graduation committee) Pintea, S. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2021-07-02 Abstract The Internet of Things (IoT) is a technology used in applications varying from home- and industrial automation to medical devices, smart vehicles, fitness trackers and many more. Such IoT networks often consist of incredibly resource-constrained devices, and are known as Low-power and Lossy Networks (LLNs). The Routing Protocol for LLNs (RPL) aims to provide a routing standard for such networks. Due to the tough performance constraints, RPL is unable to provide strong security guarantees. Many researchers are posing attacks against RPL-based networks, and with the increasing number of implementing devices, it is important that research is done to ensure message integrity and network reliability. In this paper we concern ourselves specifically with collusion attacks. We propose Hop-Count Reachability (HCR), a mitigating method against the coordinated blackhole attack. In HCR, leaf nodes periodically ping the root node with DAO messages. If the root node is reachable, it will reply with a DAO-ACK, upon which the leaf node sleeps for a period of time. When the number of missed ACKs in a certain time frame exceeds a certain threshold, the affected node may identify the attack and mitigate it by selecting a new parent. HCR may increase control packet overhead anywhere between 1.6 and 25\% depending on the chosen parameters, and successfully mitigates the coordinated blackhole attack in all scenarios where affected nodes can choose an (eventually) unaffected parent. To reference this document use: http://resolver.tudelft.nl/uuid:3fd9a90c-186c-4248-b2b9-9a0e6499882b Part of collection Student theses Document type bachelor thesis Rights © 2021 David Essaadi Files PDF _CSE3000_Research_Project ... ersion.pdf 478.57 KB Close viewer /islandora/object/uuid:3fd9a90c-186c-4248-b2b9-9a0e6499882b/datastream/OBJ/view