Empowering IoT Security: On-Device Intrusion Detection in Resource Constrained Devices

Computer Science > Cryptography and Security [Submitted on 13 May 2026] Empowering IoT Security: On-Device Intrusion Detection in Resource Constrained Devices Vasilis Ieropoulos, Eirini Anthi, Theodoros Spyridopoulos, Pete Burnap, Aftab Khan, Pietro Carnelli IoT devices particularly microcontrollers are challenged by their inherent limitations in processing capabilities, memory capacity, and energy conservation. Securing communication within IoT networks is further complicated by the heterogeneity of devices and the myriad of potential security threats. Our study introduces a lightweight model that utilises machine learning algorithms to achieve a notable detection accuracy of 99% using a decision tree method and 96% using a neural network in identifying cyber threats, including Denial of Service and Man-in-the-Middle attacks which make up the majority of the attacks these devices face. While the decision tree method offers higher accuracy, it requires more computational resources, whereas the neural network approach, despite a slightly lower accuracy, is more memory-efficient. Both methods enhance the real-time monitoring and defence of IoT networks, safeguarding the transmission of data. Additionally, our approach is tailored to conserve memory and optimise computational demands, rendering it suitable for deployment on microcontrollers with limited resources. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2605.13159 [cs.CR]   (or arXiv:2605.13159v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2605.13159 Focus to learn more Submission history From: Vasilis Ieropoulos [view email] [v1] Wed, 13 May 2026 08:23:17 UTC (6,789 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-05 Change to browse by: cs 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?)