A Practical Intrusion Detection System Trained on Ambiguously Labeled Data for Enhancing IIoT Security
Author:
Affiliation:
1. Nanyang Technological University, Singapore
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3592538.3594270
Reference37 articles.
1. Noah Apthorpe , Dillon Reisman , and Nick Feamster . 2017. A smart home is no castle: Privacy vulnerabilities of encrypted iot traffic. arXiv preprint arXiv:1705.06805 ( 2017 ). Noah Apthorpe, Dillon Reisman, and Nick Feamster. 2017. A smart home is no castle: Privacy vulnerabilities of encrypted iot traffic. arXiv preprint arXiv:1705.06805 (2017).
2. Resampling imbalanced data for network intrusion detection datasets
3. Wireless Communication and Security Issues for Cyber–Physical Systems and the Internet-of-Things
4. Ambiguously Labeled Learning Using Dictionaries
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