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Rethinking IoT Intrusion Detection: Augmenting Routing Metrics with Radio Features

arXiv Security Archived Jun 08, 2026 ✓ Full text saved

arXiv:2606.07282v1 Announce Type: new Abstract: Machine learning-based intrusion detection systems (IDS) for RPL-based IoT networks often rely solely on routing layer features, which provide only a partial view of network behaviour. In this work, we investigate whether incorporating Transmit (TX) and Receive (RX) radio features alongside the standard RPL feature set can improve detection performance in an LSTM-based IDS. We evaluate the proposed approach across three different attack types, name

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Computer Science > Cryptography and Security [Submitted on 5 Jun 2026] Rethinking IoT Intrusion Detection: Augmenting Routing Metrics with Radio Features Yichang Sun, Andreas Johnsson, Sourasekhar Banerjee Machine learning-based intrusion detection systems (IDS) for RPL-based IoT networks often rely solely on routing layer features, which provide only a partial view of network behaviour. In this work, we investigate whether incorporating Transmit (TX) and Receive (RX) radio features alongside the standard RPL feature set can improve detection performance in an LSTM-based IDS. We evaluate the proposed approach across three different attack types, namely DIS-Flooding, Local Repair, and Worst Parent under varying network sizes. The results show that incorporating TX and RX improves the IDS's overall detection performance by up to ~4% in F1-score compared with using routing-layer features alone, with the most notable gain observed for the Worst Parent attack. Comments: 4 Pages, 8 figures, Accepted to Swedish National Computer Networking Workshop (SNCNW) 2026 Subjects: Cryptography and Security (cs.CR); Networking and Internet Architecture (cs.NI) Cite as: arXiv:2606.07282 [cs.CR] (or arXiv:2606.07282v1 [cs.CR] for this version) https://doi.org/10.48550/arXiv.2606.07282 Focus to learn more Submission history From: Sourasekhar Banerejeee [view email] [v1] Fri, 5 Jun 2026 13:56:55 UTC (3,924 KB) Access Paper: view license Current browse context: cs.CR < prev | next > new | recent | 2026-06 Change to browse by: cs cs.NI References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)

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