@inproceedings{22bf4c71fb3d4696a74d24eef4405f38,
title = "Demise: Interpretable deep extraction and mutual information selection techniques for IoT intrusion detection",
keywords = "Deep learning, Feature engineering, IoT, Lightweight intrusion detection, Mutual information, Security mobility applications, Security of resource constrained devices, White-box modelling",
author = "Parker, \{Luke R.\} and Yoo, \{Paul D.\} and Asyhari, \{Taufiq A.\} and Lounis Chermak and Yoonchan Jhi and Kamal Taha",
note = "Funding Information: We are grateful to the Laboratory of Information and Communication Systems Security at George Mason University in the U.S. for providing us a copy of AWID dataset as well as their invaluable discussions; and special thanks to Samsung SDS for their constructive criticism and financial support on this work. Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery. All rights reserved.; 14th International Conference on Availability, Reliability and Security, ARES 2019 ; Conference date: 26-08-2019 Through 29-08-2019",
year = "2019",
month = aug,
day = "26",
doi = "10.1145/3339252.3340497",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
booktitle = "Proceedings of the 14th International Conference on Availability, Reliability and Security, ARES 2019",
}