In recent years, the widespread informatization and rapid data explosion have increased the demand for high-performance heterogeneous systems that integrate multiple computing cores such as CPUs, Graphics Processing Units (GPUs), Application Specific Integrated Circuits (ASICs), and Field Programmable Gate Arrays (FPGAs). The combination of CPU and GPU is particularly popular due to its versatility. However, these heterogeneous systems face significant security and privacy risks. Advances in privacy-preserving techniques, especially hardware-based Trusted Execution Environments (TEEs), offer effective protection for GPU applications. Nonetheless, the potential security risks involved in extending TEEs to GPUs in heterogeneous systems remain uncertain and need further investigation. To investigate these risks in depth, we study the existing popular GPU TEE designs and summarize and compare their key implications. Additionally, we review existing powerful attacks on GPUs and traditional TEEs deployed on CPUs, along with the efforts to mitigate these threats. We identify potential attack surfaces introduced by GPU TEEs and provide insights into key considerations for designing secure GPU TEEs. This survey is timely as new TEEs for heterogeneous systems, particularly GPUs, are being developed, highlighting the need to understand potential security threats and build both efficient and secure systems.

翻译：近年来，广泛的信息化与数据量的快速膨胀增加了对集成多种计算核心（如CPU、图形处理器、专用集成电路和现场可编程门阵列）的高性能异构系统的需求。CPU与GPU的组合因其多功能性而尤为普及。然而，这些异构系统面临着显著的安全与隐私风险。隐私保护技术的进步，特别是基于硬件的可信执行环境，为GPU应用提供了有效保护。尽管如此，在异构系统中将TEE扩展至GPU所涉及的潜在安全风险仍不明确，需要进一步研究。为深入探究这些风险，我们研究了当前主流的GPU TEE设计方案，总结并比较了其关键特性。此外，我们回顾了针对GPU以及部署在CPU上的传统TEE的现有强大攻击手段，以及缓解这些威胁的相关工作。我们识别了GPU TEE可能引入的攻击面，并对设计安全GPU TEE的关键考量因素提出了见解。本综述恰逢其时，因为面向异构系统（尤其是GPU）的新型TEE正在开发中，这凸显了理解潜在安全威胁并构建高效且安全系统的必要性。