@article{95f1cb6639f04dbdad5be624d8dc85eb,
title = "IMPACT: Impersonation Attack Detection via Edge Computing Using Deep Autoencoder and Feature Abstraction",
keywords = "IoT security, edge computing, feature engineering, intrusion detection, machine learning, mutual information",
author = "Lee, {Seo Jin} and Yoo, {Paul D.} and {Taufiq Asyhari}, A. and Yoonchan Jhi and Lounis Chermak and Yeun, {Chan Yeob} and Kamal Taha",
note = "Funding Information: This work was supported in part by the Samsung{\textquoteright}s Global Outreach Fund under Grant P10458, and in part by the Center for Cyber-Physical Systems, Khalifa University, under Grant 8474000137-RC1-C2PS-T3. Funding Information: This work was supported in part by the Samsung's Global Outreach Fund under Grant P10458, and in part by the Center for Cyber-Physical Systems, Khalifa University, under Grant 8474000137-RC1-C2PS-T3. Publisher Copyright: {\textcopyright} 2013 IEEE.",
year = "2020",
doi = "10.1109/ACCESS.2020.2985089",
language = "English",
volume = "8",
pages = "65520--65529",
journal = "IEEE Access",
issn = "2169-3536",
publisher = "IEEE",
}