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Machine Learning-Enabled IoT Security: Open Issues and Challenges Under Advanced Persistent Threats. (arXiv:2204.03433v1 [cs.CR])
April 8, 2022, 1:11 a.m. | Zhiyan Chen, Jinxin Liu, Yu Shen, Murat Simsek, Burak Kantarci, Hussein T. Mouftah, Petar Djukic
cs.LG updates on arXiv.org arxiv.org
Despite its technological benefits, Internet of Things (IoT) has cyber
weaknesses due to the vulnerabilities in the wireless medium. Machine learning
(ML)-based methods are widely used against cyber threats in IoT networks with
promising performance. Advanced persistent threat (APT) is prominent for
cybercriminals to compromise networks, and it is crucial to long-term and
harmful characteristics. However, it is difficult to apply ML-based approaches
to identify APT attacks to obtain a promising detection performance due to an
extremely small percentage among …
arxiv challenges iot learning machine machine learning security
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