基于精准自动化系统调用策略的入侵防御

L. Lam, Wei Li, T. Chiueh
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引用次数: 22

摘要

防止控制劫持攻击的一种方法是将网络应用程序的运行时系统调用与预定义的正常系统调用行为模型进行比较,并在检测到不匹配时发出警报。本文描述了一个名为PAID的系统,它可以从应用程序的源代码中自动获得准确的系统调用模式,并使用它在运行时以最小的开销检测任何异常行为。由于每个应用程序的系统调用模式都直接派生自其源代码,因此PAID永远不会引发误报警报。此外,它的假阴性率非常接近于零,因为PAID使用用户/内核堆栈上的返回地址序列来唯一地标识每个系统调用实例。在完全运行的PAID原型上的实验表明,PAID确实可以阻止所有已知的控制劫持攻击。在针对一组生产模式网络应用程序进行测试时,PAID的运行时延迟和吞吐量损失分别低于13.02%和11.52%
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accurate and Automated System Call Policy-Based Intrusion Prevention
One way to prevent control hijacking attack is to compare a network application's run-time system calls with a pre-defined normal system call behavior model, and raise an alert upon detecting a mismatch. This paper describes a system called PAID, which can automatically derive an accurate system call pattern from the source code of an application, and use it to detect any anomalous behavior at run time with minimal overhead. Because each application's system call pattern is directly derived from its source code, PAID never raises false positive alarms. Moreover, its false negative rate is very close to zero because PAID uses the sequence of return addresses on the user/kernel stack to uniquely identify each system call instance. Experiments on a fully operational PAID prototype show that PAID can indeed stop all known control hijacking attacks. The run-time latency and throughput penalty of PAID are under 13.02% and 11.52%, respectively, when it is tested against a set of production-mode network applications
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