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Automated Discovery of Mimicry Attacks

机译:自动发现模仿攻击

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摘要

Model-based anomaly detection systems restrict program execution by a predefined model of allowed system call sequences. These systems are useful only if they detect actual attacks. Previous research developed manually-constructed mimicry and evasion attacks that avoided detection by hiding a malicious series of system calls within a valid sequence allowed by the model. Our work helps to automate the discovery of such attacks. We start with two models: a program model of the application's system call behavior and a model of security-critical operating system state. Given unsafe OS state configurations that describe the goals of an attack, we then find system call sequences allowed as valid execution by the program model that produce the unsafe configurations. Our experiments show that we can automatically find attack sequences in models of programs such as wu-ftpd and passwd that previously have only been discovered manually. When undetected attacks are present, we frequently find the sequences with less than 2 seconds of computation.
机译:基于模型的异常检测系统通过允许的系统调用序列的预定义模型来限制程序执行。这些系统仅在检测到实际攻击时才有用。先前的研究开发了人工构造的模仿和规避攻击,通过在模型允许的有效序列内隐藏一系列恶意的系统调用来避免检测。我们的工作有助于自动发现此类攻击。我们从两个模型开始:应用程序的系统调用行为的程序模型和安全性至关重要的操作系统状态的模型。给定描述攻击目标的不安全OS状态配置,然后我们会找到产生不安全配置的程序模型允许作为有效执行的系统调用序列。我们的实验表明,我们可以在程序模型(例如wu-ftpd和passwd)中自动找到攻击序列,这些程序以前只是手动发现的。当出现未检测到的攻击时,我们经常发现序列少于2秒的计算时间。

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