Cloud Forensics: A Meta-Study of Challenges, Approaches, and Open Problems
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Abstract (arXiv)
In recent years, cloud computing has become popular as a cost-effective and efficient computing paradigm. Unfortunately, today's cloud computing architectures are not designed for security and forensics. To date, very little research has been done to develop the theory and practice of cloud forensics. Many factors complicate forensic investigations in a cloud environment. First, the storage system is no longer local. Therefore, even with a subpoena, law enforcement agents cannot confiscate the suspect's computer and get access to the suspect's files. Second, each cloud server contains files from many users. Hence, it is not feasible to seize servers from a data center without violating the privacy of many other users. Third, even if the data belonging to a particular suspect is identified, separating it from other users' data is difficult. Moreover, other than the cloud provider's word, there is usually no evidence that links a given data file to a particular suspect. For such challenges, clouds cannot be used to store healthcare, business, or national security related data, which require audit and regulatory compliance. In this paper, we systematically examine the cloud forensics problem and explore the challenges and issues in cloud forensics. We then discuss existing research projects and finally, we highlight the open problems and future directions in cloud forensics research area. We posit that our systematic approach towards understanding the nature and challenges of cloud forensics will allow us to examine possible secure solution approaches, leading to increased trust on and adoption of cloud computing, especially in business, healthcare, and national security. This in turn will lead to lower cost and long-term benefit to our society as a whole.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Feb 2013.
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2025Cloud Investigation Automation Framework (CIAF): An AI-Driven Approach to Cloud Forensicscited by 3
- 2026Automating Cloud Security and Forensics Through a Secure-by-Design Generative AI Frameworkcited by 1
- 2026Agentic Cloud Decoys: A Deception-Driven Framework for Autonomous Intrusion Investigationcited by 0
- 2026Agentic Cloud Decoys: A Deception-Driven Framework for Autonomous Intrusion Investigation27 Jul 2026
- 2026Automating Cloud Security and Forensics Through a Secure-by-Design Generative AI Framework5 Apr 2026
- 2025Cloud Investigation Automation Framework (CIAF): An AI-Driven Approach to Cloud Forensics1 Oct 2025