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1. A References Architecture for Human Cyber Physical Systems, Part II: Fundamental Design Principles for Human-CPS Interaction

   https://doi.org/10.1145/3622880  

   Bengler, Klaus; Damm, Werner; Luedtke, Andreas; Jochem, Reiger; Austel, Benedikt; Biebl, Bianca; Fränzle, Martin; Hagemann, Willem; Held, Moritz; Hess, David; et al (January 2024, ACM Transactions on Cyber-Physical Systems)

   Chenyang Lu (Ed.)

   As automation increases qualitatively and quantitatively in safety-critical human cyber-physical systems, it is becoming more and more challenging to increase the probability or ensure that human operators still perceive key artifacts and comprehend their roles in the system. In the companion paper, we proposed an abstract reference architecture capable of expressing all classes of system-level interactions in human cyber-physical systems. Here we demonstrate how this reference architecture supports the analysis of levels of communication between agents and helps to identify the potential for misunderstandings and misconceptions. We then develop a metamodel for safe human machine interaction. Therefore, we ask what type of information exchange must be supported on what level so that humans and systems can cooperate as a team, what is the criticality of exchanged information, what are timing requirements for such interactions, and how can we communicate highly critical information in a limited time frame in spite of the many sources of a distorted perception. We highlight shared stumbling blocks and illustrate shared design principles, which rest on established ontologies specific to particular application classes. In order to overcome the partial opacity of internal states of agents, we anticipate a key role of virtual twins of both human and technical cooperation partners for designing a suitable communication. 

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2. Design of Trustworthy Cyber–Physical–Social Systems With Discrete Bayesian Optimization

   https://doi.org/10.1115/1.4049532  

   Wang, Yan (July 2021, Journal of Mechanical Design)

   null (Ed.)

   Abstract Cyber–physical–social systems (CPSS) with highly integrated functions of sensing, actuation, computation, and communication are becoming the mainstream consumer and commercial products. The performance of CPSS heavily relies on the information sharing between devices. Given the extensive data collection and sharing, security and privacy are of major concerns. Thus, one major challenge of designing those CPSS is how to incorporate the perception of trust in product and systems design. Recently, a trust quantification method was proposed to measure the trustworthiness of CPSS by quantitative metrics of ability, benevolence, and integrity. The CPSS network architecture can be optimized by choosing a subnet such that the trust metrics are maximized. The combinatorial network optimization problem, however, is computationally challenging. Most of the available global optimization algorithms for solving such problems are heuristic methods. In this paper, a surrogate-based discrete Bayesian optimization method is developed to perform network design, where the most trustworthy CPSS network with respect to a reference node is formed to collaborate and share information with. The applications of ability and benevolence metrics in design optimization of CPSS architecture are demonstrated. 

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3. Work in Progress: Emerging From Shadows: Optimal Hidden Actuator Attack to Cyber-Physical Systems

   Miji, Md Kausar; Liu, Mengyu; Akowuah, Francis; Kong, Fanxin (May 2024, IEEE Real-Time and Embedded Technology and Applications Symposium)

   Industries are embracing information technology and constructing more robust machines known as Cyber-Physical Systems(CPS) to automate processes. CPSs are envisioned to be pervasive, coordinating, and integrating computation, sensing, actuation, and physical processes. CPSs have various applications in life-critical scenarios, where their performance and reliability can have direct impacts on human safety and well-being. However, CPSs are vulnerable to malicious attacks, and researchers have developed detectors to identify such attacks in different contexts. Surprisingly, little work has been done to detect attacks on the actuators of CPS. Furthermore, actuators face a high risk of optimal hidden attacks designed by powerful attackers, which can push them into an unsafe state without detection. To the best of our knowledge, no such attacks on actuators have been developed yet. In this paper, we design an optimal hidden attack for actuators and evaluate its effectiveness. First, we develop a mathematical model for actuators and then create a linear program for convex optimization. Second, we solve the optimization problem and simulate the optimal attack. 

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4. Design of Trustworthy Cyber-Physical-Social Systems With Discrete Bayesian Optimization

   https://doi.org/10.1115/DETC2020-22661  

   Wang, Yan (August 2020, Proceedings of ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE2020))

   null (Ed.)

   Cyber-physical-social systems (CPSS) with highly integrated functions of sensing, actuation, computation, and communication are becoming the mainstream consumer and commercial products. The performance of CPSS heavily relies on the information sharing between devices. Given the extensive data collection and sharing, security and privacy are of major concerns. Thus one major challenge of designing those CPSS is how to incorporate the perception of trust in product and systems design. Recently a trust quantification method was proposed to measure trustworthiness of CPSS by quantitative metrics of ability, benevolence, and integrity. In this paper, the applications of ability and benevolence metrics in design optimization of CPSS architecture are demonstrated. A Bayesian optimization method is developed to perform trust based CPSS network design, where the most trustworthy network with respect to a reference node can be selected to collaborate and share information with. 

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5. An Impossibility Result in Automata-Theoretic Reinforcement Learning.

   https://doi.org/10.1007/978-3-031-19992-9_3  

   Hahn, Ernst Moritz; Perez, Mateo; Schewe, Sven; Somenzi, Fabio; Trivedi, Ashutosh; Wojtczak, Dominik (October 2022, International Symposium on Automated Technology for Verification and Analysis (ATVA 2022))

   Bouajjani, A.; Holík, L.; Wu, Z. (Ed.)

   The expanding role of reinforcement learning (RL) in safety-critical system design has promoted omega-automata as a way to express learning requirements—often non-Markovian—with greater ease of expression and interpretation than scalar reward signals. When 𝜔-automata were first proposed in model-free RL, deterministic Rabin acceptance conditions were used in an attempt to provide a direct translation from omega-automata to finite state “reward” machines defined over the same automaton structure (a memoryless reward translation). While these initial attempts to provide faithful, memoryless reward translations for Rabin acceptance conditions remained unsuccessful, translations were discovered for other acceptance conditions such as suitable, limit-deterministic Buechi acceptance or more generally, good-for-MDP Buechi acceptance conditions. Yet, the question “whether a memoryless translation of Rabin conditions to scalar rewards exists” remained unresolved. This paper presents an impossibility result implying that any attempt to use Rabin automata directly (without extra memory) for model-free RL is bound to fail. To establish this result, we show a link between a class of automata enabling memoryless reward translation to closure properties of its accepting and rejecting infinity sets, and to the insight that both the property and its complement need to allow for positional strategies for such an approach to work. We believe that such impossibility results will provide foundations for the application of RL to safety-critical systems. 

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