网络物理系统的规范和反例生成

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Zhen Li, Zining Cao, Fujun Wang, Chao Xing
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引用次数: 0

摘要

网络物理系统(CPS)是将信息控制设备与物理资源整合在一起的复杂系统,可以根据形式化规范中的预期要求,通过模型检查自动进行形式化验证。模型检查中的反例是系统违反规范属性的见证,可为 CPS 的调试、控制和合成提供重要的诊断信息。为 CPS 设计合理的规范语言并生成有效的反例,可以在系统开发早期发现并解决安全漏洞。然而,CPS 涉及网络系统和物理系统之间的频繁交互,并且经常在不可靠的环境中运行,这就为具有离散、连续、时间、概率和并发行为的 CPS 的全面建模和规范语言设计提出了新的挑战。此外,在尽可能短的时间内找到具有概率行为的 CPS 的最小反例已被确定为非确定多项式完全(NP-complete)问题。尽管已经设计出许多启发式方法来应对这一挑战,但由于启发式函数难以确定,所解决反例的准确性和效率仍有待提高。我们首先介绍了混合概率时间标签转换系统(HPTLTS),为 CPS 提供了一个全面的模型。随后,我们设计了一种能描述 CPS 特性的规范语言 HPTLTS 时态逻辑(HPTLTS-TL)。此外,我们还提出了一种优化算法 CACO-A,该算法结合了蚁群优化算法(ACO)和 A 算法,可高效生成 CPS 的反例,反例用诊断子图表示。最后,我们讨论了一个典型的 CPS 例子,以证明我们方法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Specification and counterexample generation for cyber-physical systems

Specification and counterexample generation for cyber-physical systems

Cyber-Physical Systems (CPS) are complex systems that integrate information control devices with physical resources, which can be automatically and formalized verified by model checking according to the expected requirements in the formal specification. The counterexamples in model checking are witnesses to the violation of the specification properties of the system and can provide important diagnostic information for debugging, controlling, and synthesizing CPS. Designing a rational specification language for CPS and generating effective counterexamples allows security vulnerabilities to be detected and addressed early in the system development. However, CPS involve frequent interactions between cyber and physical systems and often operate in unreliable environments, which poses new challenges for comprehensive modeling and designing specification languages for CPSs with discrete, continuous, time, probabilistic, and concurrent behaviors. Moreover, finding the smallest counterexample of CPS with probabilistic behavior in the shortest possible time has been identified as a Non-Deterministic Polynomial-complete (NP-complete) problem. Although a number of heuristics have been devised to address this challenge, the accuracy and efficiency of the solved counterexamples need to be improved due to the difficulty in determining the heuristic functions. We first provide a comprehensive model for CPS by introducing the Hybrid Probabilistic Time Labeled Transition System (HPTLTS). Subsequently, we design a specification language HPTLTS Temporal Logic (HPTLTS-TL) that can describe the properties of CPS. In addition, we propose an optimization algorithm CACO-A, which combines the Ant Colony Optimization (ACO) algorithm and the A-algorithm to efficiently generate the counterexample of CPS, which is represented as the diagnostic subgraph. Finally, we discuss a typical CPS example to demonstrate the feasibility of our approach.

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来源期刊
Soft Computing
Soft Computing 工程技术-计算机:跨学科应用
CiteScore
8.10
自引率
9.80%
发文量
927
审稿时长
7.3 months
期刊介绍: Soft Computing is dedicated to system solutions based on soft computing techniques. It provides rapid dissemination of important results in soft computing technologies, a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy set theory and fuzzy systems, and chaos theory and chaotic systems. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. By linking the ideas and techniques of soft computing with other disciplines, the journal serves as a unifying platform that fosters comparisons, extensions, and new applications. As a result, the journal is an international forum for all scientists and engineers engaged in research and development in this fast growing field.
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