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Securing Real-Time Cyber-Physical Systems Using WCET-Aware Artificial Diversity

机译:使用WCET感知人工多样性确保实时网络物理系统

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Artificial software diversity is an effective way to prevent software vulnerabilities and errors to be exploited in code-reuse attacks. This is achieved by lowering the individual probability of a successful attack to a level that makes the attack unfeasible. Unfortunately, the existing approaches are not applicable to safety-critical real-time systems as they induce unacceptable performance overheads, they violate safety and timing guarantees, or they assume hardware resources which are typically not available in embedded systems. To overcome these problems, we propose a safe diversity approach that preserves the timing properties of real-time processes by controlling its impact on the worst case execution time (WCET). Our main idea is to use block-level diversity with a large, but fixed set of movable instruction sequences, and to use static WCET analysis to identify non-critical areas of code where it can safely be split into more movable instruction sequences.
机译:人工软件多样性是一种有效的方法,可以防止软件漏洞和错误在代码重用攻击中利用。这是通过降低成功攻击到攻击不可行的水平的个人概率来实现的。遗憾的是,现有方法不适用于安全关键的实时系统,因为它们诱导不可接受的性能开销,它们违反了安全性和时序保证,或者他们假设嵌入式系统中通常不可用的硬件资源。为了克服这些问题,我们提出了一种安全的分集方法,通过控制其对最坏情况执行时间(WCET)的影响来保留实时过程的时序属性。我们的主要思想是使用块级分集用大而固定的可移动指令序列,并使用静态WCET分析来识别它可以安全地分成更多可移动指令序列的非关键词的代码区域。

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