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1. Reasoning about Trustworthiness in Cyber-Physical Systems Using Ontology-Based Representation and ASP

   Thanh Hai Nguyen, Tran Cao ( November 2020 , Proceedings of the 23rd International Conference on Principles and Practice on Multi-Agent Systems (PRIMA) 2020)

   null (Ed.)

   This paper presents a framework for reasoning about trustworthiness in cyber-physical systems (CPS) that combines ontology-based reasoning and answer set programming (ASP). It introduces a formal definition of CPS and several problems related to trustworthiness of a CPS such as the problem of identification of the most vulnerable components of the system and of computing a strategy for mitigating an issue. It then shows how a combination of ontology based reasoning and ASP can be used to address the aforementioned problems. The paper concludes with a discussion of the potentials of the proposed methodologies. 

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2. Specifying and Reasoning about CPS through the Lens of the NIST CPS Framework

   https://doi.org/10.1017/S1471068422000035  

   NGUYEN, THANH HAI ; BUNDAS, MATTHEW ; SON, TRAN CAO ; BALDUCCINI, MARCELLO ; GARWOOD, KATHLEEN CAMPBELL ; GRIFFOR, EDWARD R. ( January 2022 , Theory and Practice of Logic Programming)

   Abstract This paper introduces a formal definition of a Cyber-Physical System (CPS) in the spirit of the CPS Framework proposed by the National Institute of Standards and Technology (NIST). It shows that using this definition, various problems related to concerns in a CPS can be precisely formalized and implemented using Answer Set Programming (ASP). These include problems related to the dependency or conflicts between concerns, how to mitigate an issue, and what the most suitable mitigation strategy for a given issue would be. It then shows how ASP can be used to develop an implementation that addresses the aforementioned problems. The paper concludes with a discussion of the potentials of the proposed methodologies. 

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3. A Simple Extension of Answer Set Programs to Embrace Neural Networks (Extended Abstract)

   https://doi.org/10.4204/EPTCS.325  

   Yang, Zhun ; Ishay, Adam ; Lee, Joohyung ( September 2020 , Electronic proceedings in theoretical computer science)

   Ricca, Francesco et (Ed.)

   The integration of low-level perception with high-level reasoning is one of the oldest problems in Artificial Intelligence. Today, the topic is revisited with the recent rise of deep neural networks. However, it is still not clear how complex and high-level reasoning, such as default reasoning, ontology reasoning, and causal reasoning, can be successfully computed by these approaches. The latter subject has been well-studied in the area of knowledge representation (KR), but many KR formalisms, including answer set programming (ASP), are logic-oriented and do not incorporate high-dimensional feature space as in deep learning, which limits the applicability of KR in many practical applications. 

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4. Trust Based Cyber-Physical Systems Network Design

   Wang, Yan ( August 2018 , ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference)

   Cyber-physical systems (CPS) extensively share information with each other, work collaboratively over Internet of Things, and seamlessly integrated with human society. Designing CPS requires the new consideration of design for connectivity where security, privacy, and trust are of the main concerns. Particularly trust can affect system behavior in a networked environment. In this paper, trustworthiness is quantitatively measured by the perceptions of ability, benevolence, and integrity. Ability indicates the capabilities of sensing, reasoning, and influence in a society. Benevolence measures the genuineness of intention and reciprocity in information exchange. Integrity captures the system predictability and dependability. With these criteria, trust-based CPS network design and optimization are demonstrated. 

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5. Trustworthiness in designing cyber-physical systems

   Wang, Yan ( May 2018 , Proceedings of 12th International Symposium on Tools and Methods of Competitive Engineering (TMCE2018))

   Cyber-physical systems (CPS) provide unique functions of data collection, processing, communication, and control. The advanced capabilities and functions of CPS rely on their highly networked working environment and deep interdependency. The effectiveness of their performance critically depends on what and how they share among each other. Designing a trustworthy network that CPS can work together collaboratively thus is important. In order to design trustable CPS products, quantitative measures of trustworthiness are required. In this paper, quantitative metrics of trustworthiness, including capability, benevolence, and integrity, are proposed based on a new probabilistic graph model. The proposed metrics can be calculated from either subjective perception or objective information of network topology. A design optimization framework based on the trustworthiness metrics is also demonstrated. 

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