工程拓扑感知自适应安全性:防止在运行时违反需求

Christos Tsigkanos, L. Pasquale, C. Menghi, C. Ghezzi, B. Nuseibeh
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引用次数: 26

摘要

自适应安全系统旨在保护关键资产,以应对其操作环境的变化。我们认为,结合环境拓扑的显式表示,可以对受保护资产的位置和潜在有害因子的接近程度进行推理。本文建议通过识别可能由拓扑变化引起的对安全需求的违反,并选择一组防止这种违反的安全控制来设计拓扑感知的自适应安全系统。我们的方法侧重于物理拓扑;它在运行时维护拓扑的实时表示,当资产或代理移动时,或者当物理空间的结构发生变化时,拓扑会更新。当拓扑结构发生变化时,我们展望未来系统状态的子集。当代理在物理空间内移动时,可以访问这些状态。如果在未来的系统状态中可能违反安全需求,则主动应用安全控制配置来防止系统达到这些状态。因此,系统不断适应拓扑刺激,同时保持需求的满意度。使用命题时间逻辑正式表达安全需求,在计算树逻辑(CTL)中编码空间属性。Ambient Calculus用于表示操作环境的拓扑结构——包括资产和代理的位置——以及识别从当前状态可到达的未来系统状态。使用与物理访问控制有关的实质性示例对该方法进行了演示和评估。
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Engineering topology aware adaptive security: Preventing requirements violations at runtime
Adaptive security systems aim to protect critical assets in the face of changes in their operational environment. We have argued that incorporating an explicit representation of the environment's topology enables reasoning on the location of assets being protected and the proximity of potentially harmful agents. This paper proposes to engineer topology aware adaptive security systems by identifying violations of security requirements that may be caused by topological changes, and selecting a set of security controls that prevent such violations. Our approach focuses on physical topologies; it maintains at runtime a live representation of the topology which is updated when assets or agents move, or when the structure of the physical space is altered. When the topology changes, we look ahead at a subset of the future system states. These states are reachable when the agents move within the physical space. If security requirements can be violated in future system states, a configuration of security controls is proactively applied to prevent the system from reaching those states. Thus, the system continuously adapts to topological stimuli, while maintaining requirements satisfaction. Security requirements are formally expressed using a propositional temporal logic, encoding spatial properties in Computation Tree Logic (CTL). The Ambient Calculus is used to represent the topology of the operational environment - including location of assets and agents - as well as to identify future system states that are reachable from the current one. The approach is demonstrated and evaluated using a substantive example concerned with physical access control.
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