DocumentCode
3659753
Title
An efficient classification model for detecting advanced persistent threat
Author
Saranya Chandran; Hrudya P;Prabaharan Poornachandran
Author_Institution
Amrita Center for Cybersecurity, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, India
fYear
2015
Firstpage
2001
Lastpage
2009
Abstract
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.
Keywords
"Mathematical model","Feature extraction","Malware","Vegetation","Training","Organizations"
Publisher
ieee
Conference_Titel
Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on
Print_ISBN
978-1-4799-8790-0
Type
conf
DOI
10.1109/ICACCI.2015.7275911
Filename
7275911
Link To Document