Access Restriction

Author Gardiner, Joseph ♦ Nagaraja, Shishir
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2016
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Command and control channels ♦ Botnets ♦ Data mining ♦ Machine learning ♦ Network intrusion
Abstract One of the main challenges in security today is defending against malware attacks. As trends and anecdotal evidence show, preventing these attacks, regardless of their indiscriminate or targeted nature, has proven difficult: intrusions happen and devices get compromised, even at security-conscious organizations. As a consequence, an alternative line of work has focused on detecting and disrupting the individual steps that follow an initial compromise and are essential for the successful progression of the attack. In particular, several approaches and techniques have been proposed to identify the command and control (C8C) channel that a compromised system establishes to communicate with its controller. A major oversight of many of these detection techniques is the design’s resilience to evasion attempts by the well-motivated attacker. C8C detection techniques make widespread use of a machine learning (ML) component. Therefore, to analyze the evasion resilience of these detection techniques, we first systematize works in the field of C8C detection and then, using existing models from the literature, go on to systematize attacks against the ML components used in these approaches.
Description Author Affiliation: Lancaster University, Lancaster, UK (Gardiner, Joseph; Nagaraja, Shishir)
ISSN 03600300
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2016-12-01
Publisher Place New York
e-ISSN 15577341
Journal ACM Computing Surveys (CSUR)
Volume Number 49
Issue Number 3
Page Count 39
Starting Page 1
Ending Page 39

Open content in new tab

   Open content in new tab
Source: ACM Digital Library