symbSODA: Configurable and Verifiable Orchestration Automation for Active Malware Deception

Author:

Sajid Md Sajidul Islam1ORCID,Wei Jinpeng2ORCID,Al-Shaer Ehab3ORCID,Duan Qi3ORCID,Abdeen Basel4ORCID,Khan Latifur4ORCID

Affiliation:

1. Department of Computer and Information Sciences, Towson University, MD, USA

2. Department of Software and Information Systems, University of North Carolina at Charlotte, Charlotte, NC, USA

3. S3 Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA

4. Department of Computer Science, University of Texas at Dallas, Richardson, TX, USA

Abstract

Malware is commonly used by adversaries to compromise and infiltrate cyber systems in order to steal sensitive information or destroy critical assets. Active Cyber Deception (ACD) has emerged as an effective proactive cyber defense against malware to enable misleading adversaries by presenting fake data and engaging them to learn novel attack techniques. However, real-time malware deception is a complex and challenging task because (1) it requires a comprehensive understanding of the malware behaviors at technical and tactical levels in order to create the appropriate deception ploys and resources that can leverage this behavior and mislead malware, and (2) it requires a configurable yet provably valid deception planning to guarantee effective and safe real-time deception orchestration. This article presents symbSODA, a highly configurable and verifiable cyber deception system that analyzes real-world malware using multipath execution to discover API patterns that represent attack techniques/tactics critical for deception, enables users to create their own customized deception ploys based on the malware type and objectives, allows for constructing conflict-free Deception Playbooks , and finally automates the deception orchestration to execute the malware inside a deceptive environment. symbSODA extracts Malicious Sub-graphs (MSGs) consisting of WinAPIs from real-world malware and maps them to tactics and techniques using the ATT&CK framework to facilitate the construction of meaningful user-defined deception playbooks. We conducted a comprehensive evaluation study on symbSODA using 255 recent malware samples. We demonstrated that the accuracy of the end-to-end malware deception is 95% on average, with negligible overhead using various 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%. Our study suggests that symbSODA can serve as a general-purpose Malware Deception Factory to automatically produce customized deception playbooks against arbitrary malware behavior.

Funder

Office of Naval Research

Army Research Office

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Safety, Risk, Reliability and Quality,General Computer Science

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