Abstract: With the rapid development of cloud computing, big data, and artificial intelligence, data security and privacy protection have become pressing challenges. In 2021, Arm has proposed the Confidential Compute Architecture (CCA), which introduces hardware-level isolation mechanisms to provide a trusted execution environment for sensitive computing tasks, ensuring the confidentiality and integrity of both data and code during execution. Although initial progress has been made in CCA-based studies on user-level confidential execution, device isolation, and system-level security enhancement, the field as a whole remains in its early stages. Current research remains fragmented, with limited systematic analysis of architectural evolution and underlying technical frameworks. Moreover, some studies repeatedly reimplement fundamental mechanisms without generalizing common design paradigms, while others focus primarily on functional implementation with limited exploration of potential attack surfaces and long-term risks. To address these gaps, this paper systematically analyzes the key mechanisms of CCA in confidential computing and reviews representative research advances in recent years. Specifically, it classifies design strategies and implementation approaches in areas such as execution environment extension, device isolation, application adaptation, and security enhancement. Building on typical system case studies, this work further summarizes recurring technical patterns in CCA research, including root world isolation, multi-granule memory protection tables, and the coordination of stage-2 page tables with the system memory management unit (SMMU). Finally, the paper discusses the major challenges and emerging trends faced by CCA, providing insights to guide future research and innovation in Arm-based confidential computing.