SoK:为安全使用硬件性能计数器的挑战、陷阱和危险

Sanjeev Das, Jan Werner, M. Antonakakis, M. Polychronakis, F. Monrose
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引用次数: 103

摘要

硬件性能计数器(hpc)已经在处理器中出现了十多年。这些计数器可用于监视和测量在CPU级别发生的事件。现代处理器提供了数百个可以监控的硬件事件,并且随着每个新的处理器体系结构的增加,还会增加更多的硬件事件。然而,关于如何最好地利用性能计数器来准确地监视现实环境中的事件,很少有系统的研究。特别是在安全应用中使用hpc时,测量不精确或关于测量值的错误假设可能会破坏所提供的保护。为了阐明这个问题,我们开始了长达一年的努力,以(i)研究使用性能计数器获得准确度量事件的最佳实践,(ii)了解在各种设置中使用hpc的挑战和陷阱,以及(iii)探索在不同设置和体系结构中获得一致和准确度量的方法。此外,我们还对各种论文中使用hpc的方式进行了实证评估。我们并不想就此止步,而是探讨了这些广泛使用的技术实际上是否正确地获取了性能计数器数据。作为评估的一部分,我们(iv)扩展了Weaver和McKee近10年前关于高性能计算中的非确定性的开创性工作,并将我们的发现应用于不同应用领域的56篇论文。在后续的研究中,我们发现hpc在安全应用中的接受程度与其他应用领域形成了鲜明的对比——尤其是在过去的五年里。考虑到这一点,我们从依赖hpc的安全文献中额外研究了41个具有代表性的作品,以更好地阐明我们发现的复杂性如何影响其方法和结论的可靠性和正确性。为了实现这一目标,我们(i)根据经验评估了未能适应hpc使用中的各种微妙之处如何破坏安全应用程序的有效性,特别是在漏洞预防和恶意软件检测的情况下。最后,我们展示了攻击者如何操纵hpc绕过某些安全防御。
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SoK: The Challenges, Pitfalls, and Perils of Using Hardware Performance Counters for Security
Hardware Performance Counters (HPCs) have been available in processors for more than a decade. These counters can be used to monitor and measure events that occur at the CPU level. Modern processors provide hundreds of hardware events that can be monitored, and with each new processor architecture more are added. Yet, there has been little in the way of systematic studies on how performance counters can best be utilized to accurately monitor events in real-world settings. Especially when it comes to the use of HPCs for security applications, measurement imprecisions or incorrect assumptions regarding the measured values can undermine the offered protection. To shed light on this issue, we embarked on a year-long effort to (i) study the best practices for obtaining accurate measurement of events using performance counters, (ii) understand the challenges and pitfalls of using HPCs in various settings, and (iii) explore ways to obtain consistent and accurate measurements across different settings and architectures. Additionally, we then empirically evaluated the way HPCs have been used throughout a wide variety of papers. Not wanting to stop there, we explored whether these widely used techniques are in fact obtaining performance counter data correctly. As part of that assessment, we (iv) extended the seminal work of Weaver and McKee from almost 10 years ago on non-determinism in HPCs, and applied our findings to 56 papers across various application domains. In that follow-up study, we found the acceptance of HPCs in security applications is in stark contrast to other application areas — especially in the last five years. Given that, we studied an additional representative set of 41 works from the security literature that rely on HPCs, to better elucidate how the intricacies we discovered can impact the soundness and correctness of their approaches and conclusions. Toward that goal, we (i) empirically evaluated how failure to accommodate for various subtleties in the use of HPCs can undermine the effectiveness of security applications, specifically in the case of exploit prevention and malware detection. Lastly, we showed how (ii) an adversary can manipulate HPCs to bypass certain security defenses.
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