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Adach, M., Ali, N., Hänninen, K. & Lundqvist, K. (2023). Hazard Analysis on a System of Systems using the Hazard Ontology. In: 2023 18th Annual System of Systems Engineering Conference, SoSe 2023: . Paper presented at 18th Annual System of Systems Engineering Conference, SoSe 2023, Lille 14 June 2023 through 16 June 2023. Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Hazard Analysis on a System of Systems using the Hazard Ontology
2023 (English)In: 2023 18th Annual System of Systems Engineering Conference, SoSe 2023, Institute of Electrical and Electronics Engineers Inc. , 2023Conference paper, Published paper (Refereed)
Abstract [en]

Today, well-established hazard analysis techniques are available and widely used to identify hazards for single systems in various industries. However, hazard analysis techniques for a System of Systems (SoS) are not properly investigated. SoS is a complex system where multiple systems work together to achieve a common goal. However, the interaction between systems may lead to unforeseen interactions and interdependencies between systems. This increases the difficulty of identifying and assessing system failures and potential safety hazards. In this paper, we explore whether Hazard Ontology (HO) can be applied to an SoS and whether it can identify emergent hazards, their causes, sources, and consequences. To conduct our exploration, we apply the HO to a quarry automation site (an SoS) from the construction equipment domain. The results indicate that the HO is a promising technique that facilitates the identification of emergent hazards and their components. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
a system of systems, hazard analysis, Hazard Ontology, hazards, safety, Construction equipment, System of systems, A system of system, Analysis techniques, Hazards analysis, Multiple systems, Ontology's, Potential safety hazards, System failures, System-of-systems, Ontology
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-63956 (URN)10.1109/SoSE59841.2023.10178442 (DOI)2-s2.0-85166734605 (Scopus ID)9798350327236 (ISBN)
Conference
18th Annual System of Systems Engineering Conference, SoSe 2023, Lille 14 June 2023 through 16 June 2023
Available from: 2023-08-16 Created: 2023-08-16 Last updated: 2023-09-15Bibliographically approved
Adach, M., Hänninen, K. & Lundqvist, K. (2022). A Combined Security Ontology based on the Unified Foundational Ontology. In: Proceedings - 16th IEEE International Conference on Semantic Computing, ICSC 2022: . Paper presented at 16th IEEE International Conference on Semantic Computing, ICSC 2022, 26 January 2022 through 28 January 2022 (pp. 187-194). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>A Combined Security Ontology based on the Unified Foundational Ontology
2022 (English)In: Proceedings - 16th IEEE International Conference on Semantic Computing, ICSC 2022, Institute of Electrical and Electronics Engineers Inc. , 2022, p. 187-194Conference paper, Published paper (Refereed)
Abstract [en]

While ontology comparison and alignment have been extensively researched in the last decade, there are still some challenges to these disciplines, such as incomplete ontologies, those that cover only a portion of a domain, and differences in domain modeling due to varying viewpoints. Although the literature has compared ontological concepts from the same domain, comparisons of concepts from different domains (e.g., security and safety) remain unexplored. To compare the concepts of security and safety domains, a security ontology must first be created to bridge the gap between these domains. Therefore, this paper presents a Combined Security Ontology (CSO) based on the Unified Foundational Ontology (UFO) that could be compared to or aligned with other ontologies. This CSO includes the core ontological concepts and their respective relationships that had been extracted through a previous systematic literature review. The CSO concepts and their relationships were mapped to the UFO to get a common terminology that facilitates to bridge the gap between the security and safety domains. Since the proposed CSO is based on the UFO, it could be compared to or aligned with other ontologies from different domains.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2022
Keywords
security concepts, security ontology, security relationships, UFO ontology, Different domains, Domain model, Foundational ontologies, Ontology's, Ontology-based, Security concept, Security ontologies, Security relationship, Systematic literature review, Unified foundational ontology ontology, Ontology
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-58058 (URN)10.1109/ICSC52841.2022.00039 (DOI)000835706300031 ()2-s2.0-85127609492 (Scopus ID)9781665434188 (ISBN)
Conference
16th IEEE International Conference on Semantic Computing, ICSC 2022, 26 January 2022 through 28 January 2022
Available from: 2022-04-20 Created: 2022-04-20 Last updated: 2023-08-16Bibliographically approved
Bergler, M., Kolagari, R. T. & Lundqvist, K. (2022). Case Study on the Use of the SafeML Approach in Training Autonomous Driving Vehicles. In: Lect. Notes Comput. Sci.: . Paper presented at 21st International Conference on Image Analysis and Processing, ICIAP 2022 (pp. 87-97). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>Case Study on the Use of the SafeML Approach in Training Autonomous Driving Vehicles
2022 (English)In: Lect. Notes Comput. Sci., Springer Science and Business Media Deutschland GmbH , 2022, p. 87-97Conference paper, Published paper (Refereed)
Abstract [en]

The development quality for the control software for autonomous vehicles is rapidly progressing, so that the control units in the field generally perform very reliably. Nevertheless, fatal misjudgments occasionally occur putting people at risk: such as the recent accident in which a Tesla vehicle in Autopilot mode rammed a police vehicle. Since the object recognition software which is a part of the control software is based on machine learning (ML) algorithms at its core, one can distinguish a training phase from a deployment phase of the software. In this paper we investigate to what extent the deployment phase has an impact on the robustness and reliability of the software; because just as traditional, software based on ML degrades with time. A widely known effect is the so-called concept drift: in this case, one finds that the deployment conditions in the field have changed and the software, based on the outdated training data, no longer responds adequately to the current field situation. In a previous research paper, we developed the SafeML approach with colleagues from the University of Hull, where datasets are compared for their statistical distance measures. In doing so, we detected that for simple, benchmark data, the statistical distance correlates with the classification accuracy in the field. The contribution of this paper is to analyze the applicability of the SafeML approach to complex, multidimensional data used in autonomous driving. In our analysis, we found that the SafeML approach can be used for this data as well. In practice, this would mean that a vehicle could constantly check itself and detect concept drift situation early. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2022
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 13233 LNCS
Keywords
Automotive, Autonomous driving, Machine learning, SafeML, Safety
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-58657 (URN)10.1007/978-3-031-06433-3_8 (DOI)000870308100008 ()2-s2.0-85131150606 (Scopus ID)9783031064326 (ISBN)
Conference
21st International Conference on Image Analysis and Processing, ICIAP 2022
Available from: 2022-06-08 Created: 2022-06-08 Last updated: 2022-11-09Bibliographically approved
Adach, M., Hänninen, K. & Lundqvist, K. (2022). Concepts and Relationships in Safety and Security Ontologies: A Comparative Study. In: 2022 6th International Conference on System Reliability and Safety, ICSRS 2022: . Paper presented at 6th International Conference on System Reliability and Safety, ICSRS 2022, Venice, 23 November 2022 through 25 November 2022 (pp. 357-364). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Concepts and Relationships in Safety and Security Ontologies: A Comparative Study
2022 (English)In: 2022 6th International Conference on System Reliability and Safety, ICSRS 2022, Institute of Electrical and Electronics Engineers Inc. , 2022, p. 357-364Conference paper, Published paper (Refereed)
Abstract [en]

Safety and security ontologies quickly become essential support for integrating heterogeneous knowledge from various sources. Today, there is little standardization of ontologies and almost no discussion of how to compare concepts and their relationships, establish a general approach to create relationships or model them in general. However, concepts with similar names are not semantically similar or compatible in some cases. In this case, the problem of correspondence arises among the concepts and relationships found in the ontologies. To solve this problem, a comparison between the Hazard Ontology (HO) and the Combined Security Ontology (CSO) is proposed, in which the value of equivalence between their concepts and their relationships was extracted and analyzed. Although the HO covers the concepts related to the safety domain and the CSO includes securityrelated concepts, both are based on the Unified Foundational Ontology (UFO). For this study, HO and CSO were compared, and the results were summarized in the form of comparison tables. Our main contribution involves the comparisons among the concepts in HO and CSO to identify equivalences and differences between the two. Due to the increasing number of ontologies, their mapping, merging, and alignment are primary challenges in bridging the gaps that exist between the safety and security domains. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2022
Keywords
Combined Security Ontology, comparison, concepts, Hazard Ontology, relationships, safety, security, Hazards, Comparatives studies, Concept, Ontology's, Relationship, Safety and securities, Security ontologies, Ontology
National Category
Computer Sciences
Identifiers
urn:nbn:se:mdh:diva-62283 (URN)10.1109/ICSRS56243.2022.10067740 (DOI)000981836500052 ()2-s2.0-85151690593 (Scopus ID)9781665470926 (ISBN)
Conference
6th International Conference on System Reliability and Safety, ICSRS 2022, Venice, 23 November 2022 through 25 November 2022
Available from: 2023-04-19 Created: 2023-04-19 Last updated: 2023-08-16Bibliographically approved
Gu, R., Jensen, P. G., Seceleanu, C., Enoiu, E. P. & Lundqvist, K. (2022). Correctness-Guaranteed Strategy Synthesis and Compression for Multi-Agent Autonomous Systems. Science of Computer Programming, Article ID 102894.
Open this publication in new window or tab >>Correctness-Guaranteed Strategy Synthesis and Compression for Multi-Agent Autonomous Systems
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2022 (English)In: Science of Computer Programming, ISSN 0167-6423, E-ISSN 1872-7964, article id 102894Article in journal (Refereed) Published
Abstract [en]

Planning is a critical function of multi-agent autonomous systems, which includes path finding and task scheduling. Exhaustive search-based methods such as model checking and algorithmic game theory can solve simple instances of multi-agent planning. However, these methods suffer from the state-space explosion when the number of agents is large. Learning-based methods can alleviate this problem but lack a guarantee of the correctness of the results. In this paper, we introduce MoCReL, a new version of our previously proposed method that combines model checking with reinforcement learning in solving the planning problem. The approach takes advantage of reinforcement learning to synthesize path plans and task schedules for large numbers of autonomous agents, and of model checking to verify the correctness of the synthesized strategies. Further, MoCReL can compress large strategies into smaller ones that have down to 0.05% of the original sizes, while preserving their correctness, which we show in this paper. MoCReL is integrated into a new version of UPPAAL Stratego that supports calling external libraries when running learning and verification of timed games models. 

National Category
Computer Sciences
Identifiers
urn:nbn:se:mdh:diva-58045 (URN)10.1016/j.scico.2022.102894 (DOI)000878770800001 ()2-s2.0-85141847506 (Scopus ID)
Available from: 2022-04-19 Created: 2022-04-19 Last updated: 2023-04-12Bibliographically approved
Adach, M., Hänninen, K. & Lundqvist, K. (2022). Security Ontologies: A Systematic Literature Review. In: Lecture Notes In Computer Science: 26th International Conference on Enterprise Design, Operations, and Computing, EDOC 2022. Paper presented at 26th International Conference on Enterprise Design, Operations, and Computing, EDOC 2022, Bozen-Bolzano, Italy, 3-7 October, 2022 (pp. 36-53). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>Security Ontologies: A Systematic Literature Review
2022 (English)In: Lecture Notes In Computer Science: 26th International Conference on Enterprise Design, Operations, and Computing, EDOC 2022, Springer Science and Business Media Deutschland GmbH , 2022, p. 36-53Conference paper, Published paper (Refereed)
Abstract [en]

Security ontologies have been developed to facilitate the organization and management of security knowledge. A comparison and evaluation of how these ontologies relate to one another is challenging due to their structure, size, complexity, and level of expressiveness. Differences between ontologies can be found on both the ontological and linguistic levels, resulting in errors and inconsistencies (i.e., different concept hierarchies, types of concepts, definitions) when comparing and aligning them. Moreover, many concepts related to security ontologies have not been thoroughly explored and do not fully meet security standards. By using standards, we can ensure that concepts and definitions are unified and coherent. In this study, we address these deficiencies by reviewing existing security ontologies to identify core concepts and relationships. The primary objective of the systematic literature review is to identify core concepts and relationships that are used to describe security issues. We further analyse and map these core concepts and relationships to five security standards (i.e., NIST SP 800-160, NIST SP 800-30 rev.1, NIST SP 800-27 rev.A, ISO/IEC 27001 and NISTIR 8053). As a contribution, this paper provides a set of core concepts and relationships that comply with the standards mentioned above and allow for a new security ontology to be developed.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2022
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 13585 LNCS
Keywords
Concepts, Ontologies, Relationships, Security ontology, Security standards, ISO Standards, Concept, Concept hierarchies, Ontology's, Organization and management, Relationship, Security ontologies, Size complexity, Structure sizes, Systematic literature review, Ontology
National Category
Computer Sciences
Identifiers
urn:nbn:se:mdh:diva-60551 (URN)10.1007/978-3-031-17604-3_3 (DOI)000893215100003 ()2-s2.0-85140464807 (Scopus ID)9783031176036 (ISBN)
Conference
26th International Conference on Enterprise Design, Operations, and Computing, EDOC 2022, Bozen-Bolzano, Italy, 3-7 October, 2022
Available from: 2022-11-03 Created: 2022-11-03 Last updated: 2023-08-16Bibliographically approved
Gu, R., Jensen, P. G., Poulsen, D. B., Seceleanu, C., Enoiu, E. P. & Lundqvist, K. (2022). Verifiable strategy synthesis for multiple autonomous agents: a scalable approach. International Journal on Software Tools for Technology Transfer, 24(3), 395-414
Open this publication in new window or tab >>Verifiable strategy synthesis for multiple autonomous agents: a scalable approach
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2022 (English)In: International Journal on Software Tools for Technology Transfer, ISSN 1433-2779, E-ISSN 1433-2787, Vol. 24, no 3, p. 395-414Article in journal (Refereed) Published
Abstract [en]

Path planning and task scheduling are two challenging problems in the design of multiple autonomous agents. Both problems can be solved by the use of exhaustive search techniques such as model checking and algorithmic game theory. However, model checking suffers from the infamous state-space explosion problem that makes it inefficient at solving the problems when the number of agents is large, which is often the case in realistic scenarios. In this paper, we propose a new version of our novel approach called MCRL that integrates model checking and reinforcement learning to alleviate this scalability limitation. We apply this new technique to synthesize path planning and task scheduling strategies for multiple autonomous agents. Our method is capable of handling a larger number of agents if compared to what is feasibly handled by the model-checking technique alone. Additionally, MCRL also guarantees the correctness of the synthesis results via post-verification. The method is implemented in UPPAAL STRATEGO and leverages our tool MALTA for model generation, such that one can use the method with less effort of model construction and higher efficiency of learning than those of the original MCRL. We demonstrate the feasibility of our approach on an industrial case study: an autonomous quarry, and discuss the strengths and weaknesses of the methods.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2022
National Category
Computer Sciences
Identifiers
urn:nbn:se:mdh:diva-58044 (URN)10.1007/s10009-022-00657-z (DOI)000776947000001 ()2-s2.0-85127454588 (Scopus ID)
Available from: 2022-04-19 Created: 2022-04-19 Last updated: 2024-01-17Bibliographically approved
Seceleanu, C., Enoiu, E. P., Carlson, J., Lundqvist, K., Sentilles, S., Behnam, M. & Capannini, G. (2021). Assured Cloud Platforms for Industrial Cyber-Physical Systems: The ACICS Approach. In: ACM International Conference Proceeding Series: . Paper presented at 7th Conference on the Engineering of Computer Based Systems, ECBS 2021, 26 May 2021 through 27 May 2021. Association for Computing Machinery
Open this publication in new window or tab >>Assured Cloud Platforms for Industrial Cyber-Physical Systems: The ACICS Approach
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2021 (English)In: ACM International Conference Proceeding Series, Association for Computing Machinery , 2021Conference paper, Published paper (Refereed)
Abstract [en]

With the emergence of "Industry 4.0", the integration of cloud technologies and industrial cyber-physical systems becomes increasingly important to boost productivity. The industrial cyber-physical systems infrastructures and their fusion with the cloud lead to massive amounts of data acquired for controlling particular processes, but also for supporting decision-making. Although cloud-assisted systems are increasingly important in many domains, and ensuring their dependability is crucial, existing platforms do not provide satisfactory support to meet the dependability demands of industrial applications. The overall goal of the ACICS project is to provide models, methods and tools that facilitate a substantial increase of dependability of cloud-based platforms for industrial cyber-physical applications, with respect to consistency, security and interoperability of data, timing predictability of using shared virtual resources, together with a framework of guaranteeing quality-of-service enforcement by formal analysis and verification. In this paper, we present the main conceptual ideas behind the ACICS approach.

Place, publisher, year, edition, pages
Association for Computing Machinery, 2021
Keywords
Decision making, Embedded systems, Interoperability, Quality control, Quality of service, Cloud based platforms, Cloud platforms, Cloud technologies, Cyber physicals, Formal analysis, Virtual resource, Cyber Physical System
National Category
Computer Sciences
Identifiers
urn:nbn:se:mdh:diva-58794 (URN)10.1145/3459960.3459968 (DOI)2-s2.0-85107230966 (Scopus ID)9781450390576 (ISBN)
Conference
7th Conference on the Engineering of Computer Based Systems, ECBS 2021, 26 May 2021 through 27 May 2021
Note

Conference code: 169185; Export Date: 8 June 2022; Conference Paper; Funding details: Stiftelsen för Kunskaps- och Kompetensutveckling, KKS; Funding text 1: We gratefully acknowledge the support of the Swedish Knowledge Foundation (KKS), via the synergy project ACICS.

Available from: 2022-07-13 Created: 2022-07-13 Last updated: 2022-11-08Bibliographically approved
Gu, R., Seceleanu, C., Enoiu, E. P. & Lundqvist, K. (2021). Model Checking Collision Avoidance of Nonlinear Autonomous Vehicles. In: Lecture notes in computer science, vol. 13047: . Paper presented at 24th International Symposium on Formal Methods, FM 2021, Virtual, Online, 20 November 2021 through 26 November 2021 (pp. 676-694). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>Model Checking Collision Avoidance of Nonlinear Autonomous Vehicles
2021 (English)In: Lecture notes in computer science, vol. 13047, Springer Science and Business Media Deutschland GmbH , 2021, p. 676-694Conference paper, Published paper (Refereed)
Abstract [en]

Autonomous vehicles are expected to be able to avoid static and dynamic obstacles automatically, along their way. However, most of the collision-avoidance functionality is not formally verified, which hinders ensuring such systems’ safety. In this paper, we introduce formal definitions of the vehicle’s movement and trajectory, based on hybrid transition systems. Since formally verifying hybrid systems algorithmically is undecidable, we reduce the verification of nonlinear vehicle behavior to verifying discrete-time vehicle behavior overapproximations. Using this result, we propose a generic approach to formally verify autonomous vehicles with nonlinear behavior against reach-avoid requirements. The approach provides a Uppaal timed-automata model of vehicle behavior, and uses Uppaal STRATEGO for verifying the model with user-programmed libraries of collision-avoidance algorithms. Our experiments show the approach’s effectiveness in discovering bugs in a state-of-the-art version of a selected collision-avoidance algorithm, as well as in proving the absence of bugs in the algorithm’s improved version. © 2021, Springer Nature Switzerland AG.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2021
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 13047
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-56736 (URN)10.1007/978-3-030-90870-6_37 (DOI)000758218600037 ()2-s2.0-85119885217 (Scopus ID)9783030908690 (ISBN)
Conference
24th International Symposium on Formal Methods, FM 2021, Virtual, Online, 20 November 2021 through 26 November 2021
Available from: 2021-12-14 Created: 2021-12-14 Last updated: 2022-04-22Bibliographically approved
Provenzano, L., Hänninen, K. & Lundqvist, K. (2021). Role-based approach as support for safety analysis of collaborative systems. In: Proceedings - 2021 IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing and International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2021: . Paper presented at IEEE International Conference on Dependable, Autonomic and Secure Computing (DASC 2021) (pp. 92-98).
Open this publication in new window or tab >>Role-based approach as support for safety analysis of collaborative systems
2021 (English)In: Proceedings - 2021 IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing and International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2021, 2021, p. 92-98Conference paper, Published paper (Refereed)
Abstract [en]

Modern collaborative and dynamic systems, such as System of Systems (SoS), can be considered as a set of interacting entities where the interactions are seen as the core activity fo rthese systems. The study of interactions is of importance inorder to discover emergent and inter dependent properties that impact the overall system’s behaviour. We introduce a role-based approach together with a taxonomy of roles for safety as a means to deal with emergent behaviours of high-collaborative systems that may impact the safety of the whole system. The aim ofour role-based approach is to discover the interactions that maybe harmful for the system and use them as starting point for common safety analysis techniques.

Keywords
role, role-based approach, hazard, hazard identification, safety analysis, complex system, collaborative systems, System of Systems (SoS), emergence, interdependence, safety requirements elicitation
National Category
Engineering and Technology Computer Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-56321 (URN)10.1109/DASC-PICom-CBDCom-CyberSciTech52372.2021.00028 (DOI)000942753000136 ()2-s2.0-85127579466 (Scopus ID)9781665421744 (ISBN)
Conference
IEEE International Conference on Dependable, Autonomic and Secure Computing (DASC 2021)
Projects
Serendipity
Available from: 2021-11-02 Created: 2021-11-02 Last updated: 2023-05-10Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-0904-3712

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