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A Predictive Model for Cache-Based Side Channels in Multicore and Multithreaded Microprocessors

机译:多核和多线程微处理器中基于缓存的侧通道的预测模型

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摘要

A side channel is an information channel that unintentionally communicates information about a program as a side effect of the implementation. Recent studies have illustrated the use of shared caches as side channels to extract private keys from computationally secure cryptographic applications. The cache side channel is imperfect in the sense that the attacker's ability to detect cache leakage of critical data is limited by the timing issues. Moreover, some detected leakages are due to non-critical data. Thus, it is difficult to assess the degree of vulnerability given the imperfect nature of the side-channel. Similarly, when solutions that further degrade the quality of the channel, but do not necessarily close it completely, are employed, it is difficult to evaluate their effectiveness. To address this need, this paper proposes a mathematical model to evaluate the expected leakage in a cache as a function of the cache parameters and the victim application behavior. We use simulation to quantify these parameters for typical attack scenarios to validate the model. We demonstrate that the proposed model accurately estimates side channel leakage for for AES and Blowfish encryption and decryption on a variety of cache configurations.
机译:辅助通道是一种信息通道,它会无意间传达有关程序的信息,这是实现的副作用。最近的研究表明,使用共享缓存作为辅助通道从计算安全的密码应用程序中提取私钥。从某种意义上说,攻击者检测关键数据的缓存泄漏的能力受到时序问题的限制,因此缓存侧通道是不完善的。而且,一些检测到的泄漏是由于非关键数据引起的。因此,考虑到旁通道的不完善特性,很难评估脆弱程度。类似地,当采用进一步降低通道质量但不一定完全关闭通道质量的解决方案时,很难评估其有效性。为了满足这一需求,本文提出了一种数学模型,以根据缓存参数和受害应用程序行为来评估缓存中的预期泄漏。对于典型的攻击场景,我们使用仿真来量化这些参数以验证模型。我们证明了所提出的模型可以为各种缓存配置上的AES和Blowfish加密和解密准确估计侧信道泄漏。

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