SODA: A System for Cyber Deception Orchestration and Automation

  • Md Sajidul Islam Sajid*
  • , Jinpeng Wei*
  • , Basel Abdeen
  • , Ehab Al-Shaer
  • , Md Mazharul Islam*
  • , Walter Diong
  • , Latifur Khan*
  • *Corresponding author for this work

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

28 Scopus citations

Abstract

Active Cyber Deception (ACD) has emerged as an effective proactive cyber defense technique that can mislead adversaries by presenting falsified data and allow opportunities for engaging with them to learn novel attack techniques. Adversaries often implement their attack techniques within malware and use it as the medium to steal valuable information. Comprehensive malware analysis is required to understand the malware behaviors at technical and tactical levels to create the honey resources and appropriate ploys that can leverage this behavior and mislead malware and APT adversaries. This paper presents SODA, a cyber deception orchestration system that analyzes real-world malware, discovers attack techniques, creates Deception Playbooks, a set of deception actions, and finally orchestrates the environment to deceive malware. SODA extracts Malicious Sub-graphs (MSGs) consisting of WinAPIs from real-world malware and maps them to MITRE ATT&CK techniques. This MSG-to-MITRE mapping describes how ATT&CK techniques are implemented in malware and, as a result, guides the construction of appropriate deception actions. We conducted comprehensive evaluations on SODA with 255 recent malware samples to demonstrate end-to-end deception effectiveness. We observed an average accuracy of 95% in deceiving the malware with negligible overhead for specified deception goals and strategies. Furthermore, our approach successfully extracted MSGs with a 97% recall and our MSG-to-MITRE mapping achieved a top-1 accuracy of 88.75%. More importantly, SODA can serve as a general purpose malware deception factory to automatically produce customized deception playbooks against arbitrary malware.

Original languageEnglish
Title of host publicationProceedings - 37th Annual Computer Security Applications Conference, ACSAC 2021
PublisherAssociation for Computing Machinery
Pages675-689
Number of pages15
ISBN (Electronic)9781450385794
DOIs
StatePublished - 6 Dec 2021
Externally publishedYes
Event37th Annual Computer Security Applications Conference, ACSAC 2021 - Virtual, Online, United States
Duration: 6 Dec 202110 Dec 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference37th Annual Computer Security Applications Conference, ACSAC 2021
Country/TerritoryUnited States
CityVirtual, Online
Period6/12/2110/12/21

Bibliographical note

Publisher Copyright:
© 2021 Association for Computing Machinery.

Keywords

  • Active cyber deception
  • Active cyber defense
  • Malware analysis
  • NLP
  • Text mining
  • Threat intelligence

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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