Detecting unknown attacks using context similarity

Ahmed AlEroud, George Karabatis

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The security risk of unknown attacks has been considered something that security specialists cannot measure. Contrary to hardware faults, software flaws cannot be easily identified. While it is not easy to identify unknown vulnerabilities in software systems, unknown attacks can be detected at the network level as variations of known attacks. This chapter introduces novel techniques that mainly focus on utilizing attack profiles created earlier to identify unknown attacks as a variation of known attacks.

Original languageEnglish (US)
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Verlag
Pages53-75
Number of pages23
DOIs
StatePublished - Jan 1 2017
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume691
ISSN (Print)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Detecting unknown attacks using context similarity'. Together they form a unique fingerprint.

Cite this