"An efficient classification model for detecting advanced persistent threat"

Submitted by abfox on Tue, 02/14/2017 - 10:44am

Title	"An efficient classification model for detecting advanced persistent threat"
Publication Type	Conference Paper
Year of Publication	2015
Authors	S. Chandran, Hrudya P, P. Poornachandran
Conference Name	2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
Date Published	Aug
Publisher	IEEE
ISBN Number	978-1-4799-8792-4
Accession Number	15486992
Keywords	advanced persistent threat, advanced persistent threat detection, antivirus solutions, APTs, classification model, Cyber Attacks, feature extraction, firewalls, government agencies, international trade, Intrusion detection, intrusion prevention systems, Malware, Mathematical model, Model, Organizations, pattern classification, pubcrawl170101, targeted attack, Training, Vegetation
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.
URL	http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7275911&isnumber=7275573
DOI	10.1109/ICACCI.2015.7275911
Citation Key	7275911

Groups:

Science of Security VO