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HEURISTIC AND MACHINE-LEARNING BASED METHODS TO PREVENT FINE-GRAINED CACHE SIDE-CHANNEL ATTACKS
HEURISTIC AND MACHINE-LEARNING BASED METHODS TO PREVENT FINE-GRAINED CACHE SIDE-CHANNEL ATTACKS
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机译:基于启发式和机器学习的方法来防止细颗粒的侧面通道攻击
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摘要
A system may include a processor and a memory, the processor having at least one cache as well as memory access monitoring logic. The cache may include a plurality of sets, each set having a plurality of cache lines. Each cache line includes several bits for storing information. During normal operation, the memory access monitoring logic may monitor for a memory access pattern indicative of a side-channel attack (e.g., an abnormally large number of recent CLFLUSH instructions). Upon detecting a possible side-channel attack, the memory access monitoring logic may implement one of several mitigation policies, such as, for example, restricting execution of CLFLUSH operations. Due to the nature of cache-timing side-channel attacks, this prevention of CLFLUSH may prevent attackers utilizing such attacks from gleaning meaningful information.
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