@inproceedings{290476fb4a664af59eaf12f4391e784f,
title = "A unified host-based intrusion detection framework using spark in cloud",
abstract = "The host-based intrusion detection system (HIDS) is an essential research domain of cybersecurity. HIDS examines log data of hosts to identify intrusive behaviors. The detection efficiency is a significant factor of HIDS. Traditionally, HIDS is often installed with a standalone mode. Training detection engines with a large amount of data on a single physical computer with limited computing resources may be time-consuming. Therefore, this paper offers a unified HIDS framework based on Spark and deployed in the Google cloud. The framework includes a unified machine learning pipeline to implement scalable and efficient HIDS.",
keywords = "Intrusion detection, Scalable, System call",
author = "Ming Liu and Zhi Xue and Xiangjian He",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020 ; Conference date: 29-12-2020 Through 01-01-2021",
year = "2020",
month = dec,
doi = "10.1109/TrustCom50675.2020.00026",
language = "English",
series = "Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "97--103",
editor = "Guojun Wang and Ryan Ko and Bhuiyan, {Md Zakirul Alam} and Yi Pan",
booktitle = "Proceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020",
address = "United States",
}