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Analyzing application private information leaks with privacy Petri Net

机译:使用隐私Petri Net分析应用程序私人信息泄漏

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Private information leak has been discovered in many applications and has become serious and challenging problem to cyber security. Previous works are based on two categories of road map, the one focuses on the outbound network traffic of application, the other one dives into the inside information flow of application. We incorporate application dynamic behavior analysis with network traffic analysis and present abstract model called Privacy Petri Net (PPN) which is more applicable to various applications and more meaningful to users. We apply our approach on both real world regular application and malware. The experiment result shows that our approach can effectively find categories, content, source and destination of the private information leaks for the target application.
机译:私人信息泄漏已在许多应用程序中发现,并已成为网络安全的严重且具有挑战性的问题。先前的工作基于路线图的两类,一类专注于应用程序的出站网络流量,另一类深入研究应用程序的内部信息流。我们将应用程序动态行为分析与网络流量分析相结合,并提出了称为“隐私Petri网(PPN)”的抽象模型,该模型更适用于各种应用程序,并且对用户更有意义。我们将方法应用于现实世界中的常规应用程序和恶意软件。实验结果表明,我们的方法可以有效地找到目标应用程序的私人信息泄漏的类别,内容,来源和目的地。

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