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Detecting Communication Protocol Security Flaws by Formal Fuzz Testing and Machine Learning

机译:通过正式的模糊测试和机器学习来检测通信协议安全缺陷

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Network-based fuzz testing has become an effective mechanism to ensure the security and reliability of communication protocol systems. However, fuzz testing is still conducted in an ad-hoc manner with considerable manual effort, which is mainly due to the unavailability of protocol model. In this paper we present our on-going work of developing an automated and measurable protocol fuzz testing approach that uses a formally synthesized approximate formal protocol specification to guide the testing process. We adopt the Finite State Machine protocol model and study two formal methods for protocol synthesis: an active black-box checking algorithm that has provable optimality and a passive trace minimization algorithm that is less accurate but much more efficient. We also present our preliminary results of using this method to implementations of the MSN instant messaging protocol: MSN clients Gaim (pidgin) and aMSN. Our testing reveals some serious reliability and security flaws by automatically crashing both of them.
机译:基于网络的模糊测试已成为确保通信协议系统的安全性和可靠性的有效机制。但是,模糊测试仍然是通过即席方式进行的,需要大量的人工,这主要是由于协议模型不可用。在本文中,我们介绍了正在进行的工作,该工作正在开发一种自动化且可测量的协议模糊测试方法,该方法使用正式合成的近似正式协议规范来指导测试过程。我们采用有限状态机协议模型,并研究了两种用于协议合成的正式方法:具有可证明的最优性的主动黑盒检查算法和精度较低但效率更高的被动跟踪最小化算法。我们还介绍了使用此方法实现MSN即时消息传递协议的初步结果:MSN客户端Gaim(pidgin)和aMSN。我们的测试通过自动将它们都崩溃,揭示了一些严重的可靠性和安全性缺陷。

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