期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2020
卷号：11
期号：5
DOI：10.14569/IJACSA.2020.0110504
出版社：Science and Information Society (SAI)
摘要：APT (Advanced Persistent Threat) attack is a form of dangerous attack, it has clear intentions and targets. APT uses a variety of sophisticated, complex methods and technologies to attack on targets to gain confidential, sensitive information. Currently, the problem of detecting APT attacks still faces many challenges. The reason is APT attacks are designed specifically for each specific target, so it is difficult to detect them based on experiences or predefined rules. There are many different methods that are researched and applied to detect early signs of APT attacks in an organization. Today, one method of great concern is analyzing connections to detect a control server (C&C Server) in the APT attack campaign. This method has great practical significance because we just need to detect early the connection of malware to the control server, we will prevent quickly attack campaigns. In this paper, we propose a method to detect C&C Server based on network traffic analysis using machine learning.
关键词：Advanced Persistent Threat (APT); abnormal behavior; network traffic; machine learning; APT detection; Control Server (C&C Server)
