Research on Cloud Forensic Techniques focuses on developing methods and tools to investigate, collect, preserve, and analyze digital evidence in cloud computing environments while addressing the unique challenges posed by virtualization, multi-tenancy, distributed storage, and dynamic resource allocation. This area addresses issues such as data volatility, jurisdictional constraints, and the lack of physical access to cloud infrastructure. Key research directions include forensic data acquisition and preservation from virtual machines and containers, log analysis and correlation across distributed cloud services, and automated forensic frameworks for real-time investigation. Other emerging topics involve cloud-specific evidence integrity verification, privacy-preserving forensic methods, and integration of machine learning and AI for anomaly detection and event reconstruction. Additionally, research on cloud forensic readiness, multi-cloud and hybrid cloud forensic frameworks, blockchain-assisted auditing, and SLA-compliant forensic procedures represents significant avenues for advancing reliable, efficient, and legally admissible forensic investigation in cloud computing systems.