Digital Forensics vs. Anti-Digital Forensics: Techniques, Limitations and Recommendations

Abstract

The number of cyber attacks has increased tremendously in the last few years. This resulted into both human and financial losses at the individual and organization levels. Recently, cyber-criminals are leveraging new skills and capabilities by employing anti-forensics activities, techniques and tools to cover their tracks and evade any possible detection. Consequently, cyber-attacks are becoming more efficient and more sophisticated. Therefore, traditional cryptographic and non-cryptographic solutions and access control systems are no longer enough to prevent such cyber attacks, especially in terms of acquiring evidence for attack investigation. Hence, the need for well-defined, sophisticated, and advanced forensics investigation tools are highly required to track down cyber criminals and to reduce the number of cyber crimes. This paper reviews the different forensics and anti-forensics methods, tools, techniques, types, and challenges, while also discussing the rise of the anti-anti-forensics as a new forensics protection mechanism against anti-forensics activities. This would help forensics investigators to better understand the different anti-forensics tools, methods and techniques that cyber criminals employ while launching their attacks. Moreover, the limitations of the current forensics techniques are discussed, especially in terms of issues and challenges. Finally, this paper presents a holistic view from a literature point of view over the forensics domain and also helps other fellow colleagues in their quest to further understand the digital forensics domain.

The current landscape of digital forensics employing machine learning approaches: A Review

“…e) Employing Modern Technology: Encompasses the cooperation with contemporary technology like artificial intelligence and machine learning to enhance the examination of evidence and expedite investigation procedures [21] . f) Digital fingerprint analysis: Digital forensics allows for the examination of digital fingerprints and facial features in order to prove identity and aid in the identification of remains [22] . g) Developments in Machine Learning: The accuracy of medical judgements in the forensic sector is being improved by advances in machine learning and data analysis techniques [23] .…”

Toward a Conflict Resolution Protocol for Cloud Forensics Investigation

“…Furthermore, the authors presented a case study that demonstrated the utilization of Google Documents evidence collection and analysis tools, as well as cloud-based evidence acquisition methods. Yaacoub et al [19] have conducted research on anti-forensics tactics in the context of cloud computing. The authors developed a taxonomy for categorizing the anti-forensic efforts in cloud computing.…”