Print Email Facebook Twitter IoT-KEEPER Title IoT-KEEPER: Detecting Malicious IoT Network Activity Using Online Traffic Analysis at the Edge Author Hafeez, Ibbad (University of Helsinki) Antikainen, Markku (Aalto University) Ding, Aaron Yi (TU Delft Information and Communication Technology) Tarkoma, Sasu (University of Helsinki) Date 2020 Abstract IoT devices are notoriously vulnerable even to trivial attacks and can be easily compromised. In addition, resource constraints and heterogeneity of IoT devices make it impractical to secure IoT installations using traditional endpoint and network security solutions. To address this problem, we present IoT-Keeper, a lightweight system which secures the communication of IoT. IoT-Keeper uses our proposed anomaly detection technique to perform traffic analysis at edge gateways. It uses a combination of fuzzy C-means clustering and fuzzy interpolation scheme to analyze network traffic and detect malicious network activity. Once malicious activity is detected, IoT-Keeper automatically enforces network access restrictions against IoT device generating this activity, and prevents it from attacking other devices or services. We have evaluated IoT-Keeper using a comprehensive dataset, collected from a real-world testbed, containing popular IoT devices. Using this dataset, our proposed technique achieved high accuracy (≈0.98) and low false positive rate (≈0.02) for detecting malicious network activity. Our evaluation also shows that IoT-Keeper has low resource footprint, and it can detect and mitigate various network attacks - without requiring explicit attack signatures or sophisticated hardware. Subject activity detectionanomaly detectionIoTnetworkprivacysecuritytraffic classification To reference this document use: http://resolver.tudelft.nl/uuid:b917bb85-b1ce-4608-a6f1-83f26d22007a DOI https://doi.org/10.1109/TNSM.2020.2966951 ISSN 1932-4537 Source IEEE Transactions on Network and Service Management, 17 (1), 45-59 Part of collection Institutional Repository Document type journal article Rights © 2020 Ibbad Hafeez, Markku Antikainen, Aaron Yi Ding, Sasu Tarkoma Files PDF IoT_KEEPER.pdf 886.91 KB Close viewer /islandora/object/uuid:b917bb85-b1ce-4608-a6f1-83f26d22007a/datastream/OBJ/view