首页> 外国专利> 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

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

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.
机译:一种系统可以包括处理器和存储器,该处理器具有至少一个高速缓存以及存储器访问监视逻辑。高速缓存可以包括多个集合,每个集合具有多个高速缓存行。每条高速缓存行包括几个用于存储信息的位。在正常操作期间,存储器访问监视逻辑可以监视指示侧通道攻击(例如,异常大量的最近的CLFLUSH指令)的存储器访问模式。在检测到可能的旁信道攻击时,存储器访问监视逻辑可以实施几种缓解策略之一,例如,限制CLFLUSH操作的执行。由于缓存定时侧信道攻击的性质,对CLFLUSH的这种预防可能会阻止利用此类攻击的攻击者收集有意义的信息。

著录项

  • 公开/公告号WO2020005450A1

    专利类型

  • 公开/公告日2020-01-02

    原文格式PDF

  • 申请/专利权人 INTEL CORPORATION;

    申请/专利号WO2019US34442

  • 发明设计人 BASAK ABHISHEK;CHEN LI;SAHITA RAVI;

    申请日2019-05-29

  • 分类号G06F12/14;G06F12/0891;G06F21/55;

  • 国家 WO

  • 入库时间 2022-08-21 11:13:58

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