@inproceedings{a9fc5d3ee69741579df8011d03238d1a,
title = "A New Approach to Detecting Bot Attack Activity Scenario",
abstract = "Botnets are a dangerous threat to computer networks. A botnet consists of a bot-master and bot-client connected and communicated through command and control (C&C) servers. When the bot attacks and infects the target computer, it performs several activities. Nevertheless, the introduced model may not detect the connection between one activity and others as a whole botnet attack scenario. The connection between activities is required to get the attack step carried out by each bot. This paper proposes a new approach to detect linkages between bot activities by analyzing the network traffic flows and obtaining a bot attack scenario. The analysis is carried out by finding the frequency of each activity that is sequentially connected. The results show that the proposed model successfully detects interrelated bot activity scenarios based on its pattern.",
keywords = "Bot activity, Bot network, Intrusion detection system, Network security",
author = "Hostiadi, {Dandy Pramana} and Tohari Ahmad and Waskitho Wibisono",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 12th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2020 and 16th International Conference on Information Assurance and Security, IAS 2020 ; Conference date: 15-12-2020 Through 18-12-2020",
year = "2021",
doi = "10.1007/978-3-030-73689-7_78",
language = "English",
isbn = "9783030736880",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "823--835",
editor = "Ajith Abraham and Yukio Ohsawa and Niketa Gandhi and Jabbar, {M. A.} and Abdelkrim Haqiq and Se{\'a}n McLoone and Biju Issac",
booktitle = "Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2020",
address = "Germany",
}