实用和安全的PCM系统通过在线检测恶意写流

Moinuddin K. Qureshi, André Seznec, L. Lastras, M. Franceschini
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引用次数: 101

摘要

在未来几年内,相变存储器(PCM)可能成为主存储系统设计的一种可行的替代方案。然而,PCM的写入持久性有限。因此,PCM作为主存技术的未来采用将取决于磨损均衡的实用解决方案的可用性,以避免使用不均匀,特别是在潜在恶意用户存在的情况下。第一代磨损均衡算法是为典型的工作负载而设计的,并且在试图连续写入同一行的恶意访问模式下显着缩短了寿命。最近提出了安全磨损均衡算法。它们可以处理此类恶意攻击,但要求以比典型应用程序所需的速率高几个数量级的速率进行损耗均衡,从而导致非常高的写入开销,可能会损害系统的整体性能。本文提出了一个实用的损耗均衡框架,该框架可以在攻击下提供数年的使用寿命,同时对于典型应用程序来说,仍然可以忽略不计(<1%)的编写开销。它使用一个简单的和新颖的在线攻击检测器电路,以适应磨损均衡的速率取决于内存参考流的属性,从而获得两全其美-低开销的典型应用和数年的寿命下的攻击。提出的攻击检测器需要68字节的存储开销,可以有效地估计攻击的严重程度,适用于各种磨损均衡算法,并将最近提出的几种磨损均衡算法的写入开销降低了16 - 128倍。在线攻击检测范例还支持其他预防措施。
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Practical and secure PCM systems by online detection of malicious write streams
Phase Change Memory (PCM) may become a viable alternative for the design of main memory systems in the next few years. However PCM suffers from limited write endurance. Therefore future adoption of PCM as a technology for main memory will depend on the availability of practical solutions for wear leveling that avoids uneven usage especially in the presence of potentially malicious users. First generation wear leveling algorithms were designed for typical workloads and have significantly reduced lifetime under malicious access patterns that try to write to the same line continuously. Secure wear leveling algorithms were recently proposed. They can handle such malicious attacks, but require that wear leveling is done at a rate that is orders of magnitude higher than what is sufficient for typical applications, thereby incurring significantly high write overhead, potentially impairing overall performance system. This paper proposes a practical wear-leveling framework that can provide years of lifetime under attacks while still incurring negligible (<1%) write overhead for typical applications. It uses a simple and novel Online Attack Detector circuit to adapt the rate of wear leveling depending on the properties of the memory reference stream, thereby obtaining the best of both worlds — low overhead for typical applications and years of lifetime under attacks. The proposed attack detector requires a storage overhead of 68 bytes, is effective at estimating the severity of attacks, is applicable to a wide variety of wear leveling algorithms, and reduces the write overhead of several recently proposed wear leveling algorithms by 16x–128x. The paradigm of online attack detection enables other preventive actions as well.
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