An efficient classification model for detecting advanced persistent threat
Publication Type:Conference Paper
Source:2015 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015, Institute of Electrical and Electronics Engineers Inc., p.2001-2009 (2015)
Keywords:Advanced Persistent Threat, Anti virus, Classification models, Computer system firewalls, Cyber-attacks, Government agencies, Information science, International trade, Intrusion detection, Intrusion prevention systems, Mercury (metal), Models, Sensitive datas, targeted attack
Among most of the cyber attacks that occured, the most drastic are advanced persistent threats. APTs are differ from other attacks as they have multiple phases, often silent for long period of time and launched by adamant, well-funded opponents. These targeted attacks mainly concentrated on government agencies and organizations in industries, as are those involved in international trade and having sensitive data. APTs escape from detection by antivirus solutions, intrusion detection and intrusion prevention systems and firewalls. In this paper we proposes a classification model having 99.8% accuracy, for the detection of APT. © 2015 IEEE.
cited By 0; Conference of International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015 ; Conference Date: 10 August 2015 Through 13 August 2015; Conference Code:115835