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首页> 外文期刊>IEEE transactions on information forensics and security >Stealthy Attacks in Dynamical Systems: Tradeoffs Between Utility and Detectability With Application in Anonymous Systems
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Stealthy Attacks in Dynamical Systems: Tradeoffs Between Utility and Detectability With Application in Anonymous Systems

机译:动态系统中的隐形攻击:实用程序和可检测性之间的权衡以及在匿名系统中的应用

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Cyber physical systems which integrate physical system dynamics with digital cyber infrastructure are envisioned to transform our core infrastructural frameworks, such as the smart electricity grid, transportation networks, and advanced manufacturing. This integration, however, exposes the physical system functioning to the security vulnerabilities of cyber communication. Both scientific studies and real-world examples have demonstrated the impact of data injection attacks on complex systems, including the Internet, the smart electricity grid, and air traffic systems. In this paper, an abstract theoretical framework is proposed to study data injection/modification attacks on Markov modeled dynamical systems from the perspective of an adversary. Typical data injection attacks focus on one shot attacks by adversary and the non-detectability of such attacks under static assumptions. In this paper, we study dynamic data injection attacks where the adversary is capable of modifying a temporal sequence of data and the physical controller is equipped with prior statistical knowledge about the data arrival process to detect the presence of an adversary. The goal of the adversary is to modify the arrivals to minimize a utility function of the controller while minimizing the detectability of his presence as measured by the K-L divergence between the prior and posterior distribution of the arriving data. The tradeoff between these two metrics-controller utility and the detectability cost-is studied analytically for different underlying dynamics. The proposed framework is then applied to a practical problem in data networks where a router tries to hide the path of traffic flow from timing analysis by an active adversary who can modify the timing of an incoming packet stream. This problem is studied from the adversary perspective wherein the goal is to balance two costs-the adversary's detectability cost measured by the K-L divergence and the network privacy cost measured by the maximum length of the packet stream whose paths can be hidden by a memory limited router.
机译:设想将物理系统动力学与数字网络基础设施相集成的网络物理系统将转变我们的核心基础架构框架,例如智能电网,交通网络和先进制造。但是,这种集成使物理系统的功能暴露于网络通信的安全漏洞中。科学研究和实际示例均展示了数据注入攻击对复杂系统(包括Internet,智能电网和空中交通系统)的影响。本文提出了一个抽象的理论框架,旨在从对手的角度研究对马尔可夫模型动力学系统的数据注入/修改攻击。典型的数据注入攻击着眼于对手的一发式攻击,以及在静态假设下这种攻击的不可检测性。在本文中,我们研究了动态数据注入攻击,其中对手能够修改数据的时间顺序,而物理控制器具备有关数据到达过程的先验统计知识,可以检测到对手的存在。对手的目标是修改到达的位置,以最小化控制器的效用函数,同时最小化通过到达数据的前后分布之间的K-L散度测量的他的存在的可检测性。针对不同的基础动力学分析地研究了这两个度量控制器效用和可检测性成本之间的折衷。然后,将所提出的框架应用于数据网络中的实际问题,在该问题中,路由器试图通过主动对手来隐藏流量流的路径以免进行时序分析,主动对手可以修改传入数据包流的时序。从对手的角度研究此问题,其中目标是平衡两个成本:通过KL散度衡量的对手的可检测性成本,以及通过路径可被内存受限的路由器隐藏的数据包流的最大长度所衡量的网络隐私成本。 。

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