Research on Anti-Forensic Techniques in Cloud Computing focuses on understanding, detecting, and mitigating methods that adversaries use to hinder, mislead, or evade forensic investigations in cloud environments. This area addresses challenges arising from virtualization, multi-tenancy, dynamic resource allocation, distributed storage, and the inherent lack of physical access, which make cloud systems particularly susceptible to anti-forensic activities. Key research directions include identifying and analyzing data obfuscation, log tampering, and secure deletion techniques employed by malicious actors, as well as the development of forensic-resistant cloud storage and communication channels. Other emerging topics involve designing detection frameworks for anti-forensic behaviors, integrating machine learning for anomaly and tampering detection, and creating resilient logging and auditing mechanisms. Additionally, research on countermeasures for anti-forensic attacks, blockchain-enabled evidence integrity, and anti-tampering forensic frameworks represents significant avenues for advancing secure, reliable, and effective cloud forensic investigations.