Precision Countermeasures for GPU Side Channels Using Shader Execution Pattern Analysis

Graphics Processing Units (GPUs) have become increasingly susceptible to side-channel attacks, compromising the security of sensitive information processed on these devices. This paper presents a novel approach to mitigating GPU side-channel vulnerabilities using shader execution pattern analysis. The proposed technique enables the development of precision countermeasures that effectively obscure the timing and power consumption patterns exploited by adversaries. By leveraging insights gained from analysing shader execution patterns, we develop targeted countermeasures that combine data-dependent execution balancing, power consumption smoothing, and dynamic noise injection to provide comprehensive protection against a wide range of side-channel attacks. Experimental results demonstrate the efficacy of the proposed method in significantly reducing the leakage of sensitive information through GPU side channels while incurring minimal performance overhead. The findings of this research contribute to the advancement of GPU security and the protection of sensitive data in graphics-intensive applications, paving the way for more secure and trustworthy computing environments.