| Title | Detecting and Mitigating Jamming Attacks in IoT Networks Using Self-Adaptation |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Reynvoet, Maxim, Gheibi, Omid, Quin, Federico, Weyns, Danny |
| Conference Name | 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) |
| Date Published | sep |
| Keywords | Adaptation models, Autonomic Security, composability, Computer architecture, distributed computing, Internet of Things, IoT, jamming, jamming attacks, Monitoring, pubcrawl, resilience, Resiliency, self-adaptation, wireless networks |
| Abstract | Internet of Things (IoT) networks consist of small devices that use a wireless communication to monitor and possibly control the physical world. A common threat to such networks are jamming attacks, a particular type of denial of service attack. Current research highlights the need for the design of more effective and efficient anti-jamming techniques that can handle different types of attacks in IoT networks. In this paper, we propose DeMiJA, short for Detection and Mitigation of Jamming Attacks in IoT, a novel approach to deal with different jamming attacks in IoT networks. DeMiJA leverages architecture-based adaptation and the MAPE-K reference model (Monitor-Analyze-Plan-Execute that share Knowledge). We present the general architecture of DeMiJA and instantiate the architecture to deal with jamming attacks in the DeltaIoT exemplar. The evaluation shows that DeMiJA can handle different types of jamming attacks effectively and efficiently, with neglectable overhead. |
| DOI | 10.1109/ACSOSC56246.2022.00019 |
| Citation Key | reynvoet_detecting_2022 |
Detecting and Mitigating Jamming Attacks in IoT Networks Using Self-Adaptation