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From Speculation To Security: Practical And Efficient Information Flow Tracking Using Speculative Hardware

机译:从推测到安全:使用推测性硬件进行实用,高效的信息流跟踪

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Dynamic information flow tracking (also known as taint tracking) is an appealing approach to combat various security attacks. However, the performance of applications can severely degrade without hardware support for tracking taints. This paper observes that information flow tracking can be efficiently emulated using deferred exception tracking in microprocessors supporting speculative execution. Based on this observation, we propose SHIFT, a low-overhead, software-based dynamic information flow tracking system to detect a wide range of attacks. The key idea is to treat tainted state (describing untrusted data) as speculative state (describing deferred exceptions). SHIFT leverages existing architectural support for speculative execution to track tainted state in registers and needs to instrument only load and store instructions to track tainted state in memory using a bitmap, which results in significant performance advantages. Moreover, by decoupling mechanisms for taint tracking from security policies, SHIFT can detect a wide range of exploits, including high-level semantic attacks. We have implemented SHIFT using the Itanium processor, which has support for deferred exceptions, and by modifying GCC to instrument loads and stores. A security assessment shows that SHIFT can detect both low-level memory corruption exploits as well as high-level semantic attacks with no false positives. Performance measurements show that SHIFT incurs about 1% overhead for server applications. The performance slowdown for SPEC-INT2000 is 2.81X and 2.27X for tracking at byte-level and word-level respectively. Minor architectural improvements to the Itanium processor (adding three simple instructions) can reduce the performance slowdown down to 2.32X and 1.8X for byte-level and word-level tracking, respectively.
机译:动态信息流跟踪(也称为污点跟踪)是一种抗击各种安全攻击的诱人方法。但是,如果没有用于跟踪污点的硬件支持,应用程序的性能就会严重下降。本文观察到,在支持推测执行的微处理器中,可以使用延迟异常跟踪来有效地模拟信息流跟踪。基于此观察结果,我们提出了SHIFT,这是一种低开销,基于软件的动态信息流跟踪系统,可以检测各种攻击。关键思想是将污染状态(描述不受信任的数据)视为推测状态(描述延迟的异常)。 SHIFT利用现有的体系结构支持来进行推测性执行,以跟踪寄存器中的污染状态,并且只需要使用位图对加载和存储指令进行检测,即可跟踪内存中的污染状态,从而获得显着的性能优势。此外,通过从安全策略中分离出用于污点跟踪的机制,SHIFT可以检测到各种各样的漏洞,包括高级语义攻击。我们已经使用Itanium处理器实现了SHIFT,该处理器具有对延迟异常的支持,并通过修改GCC来检测和加载仪器。安全评估表明,SHIFT可以检测到低级别的内存破坏漏洞以及没有误报的高级语义攻击。性能测量表明,SHIFT对于服务器应用程序产生约1%的开销。对于字节级和字级跟踪,SPEC-INT2000的性能下降分别为2.81X和2.27X。对Itanium处理器的较小体系结构改进(添加了三个简单的指令)可以将字节级和字级跟踪的性能分别降低到2.32倍和1.8倍。

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