Demo: Akatosh: Automated cyber incident verification and impact analysis

Jared M. Smith, Elliot Greenlee, Aaron Ferber

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Akatosh, a U.S. Department of Homeland Security Transition to Practice Program (TTP) project developed by Oak Ridge National Laboratory with industry and academic partnership, enables automated, real-time forensic analysis of endpoints a.er malwarea .acks and other cyber security incidents by automatically maintaining detailed snapshots of host-level activity on endpoints over time. It achieves this by integrating intrusion detection systems (IDS) with forensic tools. .e combination allows Akatosh to collect vast amounts of endpoint data and assists in verifying, tracking, and analyzing endpoints in real time. .is provides operations personnel and analysts as well as managers and executives with continuous feedback on the impact of malicious so.ware and other security incidents on endpoints in their network.

Original languageEnglish
Title of host publicationCCS 2017 - Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security
PublisherAssociation for Computing Machinery
Pages2463-2465
Number of pages3
ISBN (Electronic)9781450349468
DOIs
StatePublished - Oct 30 2017
Externally publishedYes
Event24th ACM SIGSAC Conference on Computer and Communications Security, CCS 2017 - Dallas, United States
Duration: Oct 30 2017Nov 3 2017

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)1543-7221

Conference

Conference24th ACM SIGSAC Conference on Computer and Communications Security, CCS 2017
Country/TerritoryUnited States
CityDallas
Period10/30/1711/3/17

Keywords

  • Breach Remediation
  • Endpoint Security
  • Forensic Analysis
  • Incident Response

Fingerprint

Dive into the research topics of 'Demo: Akatosh: Automated cyber incident verification and impact analysis'. Together they form a unique fingerprint.

Cite this