@inproceedings{4265e4adc9644e7c9582beab876c936a,
title = "D{\"I}oT: A Federated Self-learning Anomaly Detection System for IoT",
keywords = "Internet of Things, invasive software, learning (artificial intelligence), security of data, telecommunication security, federated self-learning anomaly detection system, vulnerable IoT devices, existing intrusion detection techniques, D{\"I}oT, autonomous self-learning distributed system, device-type-specific communication profiles, federated learning approach, anomaly-detection-based intrusion detection, off-the-shelf IoT devices, detecting devices, Security, Logic gates, Anomaly detection, Malware, Data models, Monitoring, Internet of Things, IoT security, IoT malware, anomaly detection, federated deep learning, self-learning",
author = "Nguyen, {T. D.} and S. Marchal and M. Miettinen and H. Fereidooni and N. Asokan and A. Sadeghi",
year = "2019",
doi = "10.1109/ICDCS.2019.00080",
language = "English",
series = "International Conference on Distributed Computing Systems",
publisher = "IEEE",
pages = "756--767",
booktitle = "2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)",
address = "United States",
note = "International Conference on Distributed Computing Systems , ICDCS ; Conference date: 07-07-2019 Through 10-07-2019",
}