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  • 1.
    Atif, Yacine
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Internet of Things Approach to Cloud-Based Smart Car Parking2016In: The 7th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2016)/The 6th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH-2016)/Affiliated Workshops / [ed] Elhadi Shakshuki, Elsevier, 2016, Vol. 98, p. 193-198Conference paper (Refereed)
    Abstract [en]

    Concerns for parking are becoming imminent to best support the urban core. These persistent parking problems could be turned into new opportunities, brought by current trends in meeting the globally connected continuum. This paper reveals a work-in- progress to capitalize on private land properties for parking, in order to relieve stress on public agencies, create new sources of revenue, and enlist new entities in the intermediary market. These intermediaries, labelled as Parking Service Providers (or PSPs) play a broker role through advertising parking lots on a shared cloud platform. To streamline these business collaborations and related processes, physical parking lots are augmented with Internet connectivity allowing cloud-provided applications to congregate these lots into a larger inventory. The Internet of Things (IoT) paradigm expands the scope of cloud-based intelligent car parking services in smart cities, with novel applications that better regulate car-parking related traffic. This paper presents a work-in-progress agenda that contributes to new business solutions and state-of-the-art research impacts. We reveal a multi-layered system of PSP-business model through interdisciplinary research blocks where original results are expected to be made at each layer.

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  • 2.
    Atif, Yacine
    et al.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Jeusfeld, Manfred
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Andler, Sten F.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Yuning, Jiang
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Brax, Christoffer
    CombiTech AB, Skövde, Sweden.
    Gustavsson, Per M.
    CombiTech AB, Skövde, Sweden.
    Cyber-Threat Intelligence Architecture for Smart-Grid Critical Infrastructures Protection2017Conference paper (Refereed)
    Abstract [en]

    Critical infrastructures (CIs) are becoming increasingly sophisticated with embedded cyber-physical systems (CPSs) that provide managerial automation and autonomic controls. Yet these advances expose CI components to new cyber-threats, leading to a chain of dysfunctionalities with catastrophic socio-economical implications. We propose a comprehensive architectural model to support the development of incident management tools that provide situation-awareness and cyber-threats intelligence for CI protection, with a special focus on smart-grid CI. The goal is to unleash forensic data from CPS-based CIs to perform some predictive analytics. In doing so, we use some AI (Artificial Intelligence) paradigms for both data collection, threat detection, and cascade-effects prediction. 

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  • 3.
    Atif, Yacine
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jiang, Yuning
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten F.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Brax, Christoffer
    Combitech.
    Haglund, Daniel
    Combitech.
    Lindström, Björn
    Combitech.
    Cyber-threat analysis for Cyber-Physical Systems: Technical report for Package 4, Activity 3 of ELVIRA project2018Report (Other academic)
    Abstract [en]

    Smart grid employs ICT infrastructure and network connectivity to optimize efficiency and deliver new functionalities. This evolu- tion is associated with an increased risk for cybersecurity threats that may hamper smart grid operations. Power utility providers need tools for assessing risk of prevailing cyberthreats over ICT infrastructures. The need for frameworks to guide the develop- ment of these tools is essential to define and reveal vulnerability analysis indicators. We propose a data-driven approach for design- ing testbeds to evaluate the vulnerability of cyberphysical systems against cyberthreats. The proposed framework uses data reported from multiple components of cyberphysical system architecture layers, including physical, control, and cyber layers. At the phys- ical layer, we consider component inventory and related physi- cal flows. At the control level, we consider control data, such as SCADA data flows in industrial and critical infrastructure control systems. Finally, at the cyber layer level, we consider existing secu- rity and monitoring data from cyber-incident event management tools, which are increasingly embedded into the control fabrics of cyberphysical systems.

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  • 4.
    Atif, Yacine
    et al.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Jiang, Yuning
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Jeusfeld, Manfred
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Andler, Sten
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Nero, Eva
    Combitech, Sweden.
    Brax, Christoffer
    Combitech, Sweden.
    Haglund, Daniel
    Combitech, Sweden.
    Multi-agent Systems for Power Grid Monitoring: Technical report for Package 4.1 of ELVIRA project2018Report (Other academic)
    Abstract [en]

    This document reports a technical description of ELVIRA project results obtained as part of Work- package 4.1 entitled “Multi-agent systems for power Grid monitoring”. ELVIRA project is a collaboration between researchers in School of IT at University of Skövde and Combitech Technical Consulting Company in Sweden, with the aim to design, develop and test a testbed simulator for critical infrastructures cybersecurity. This report outlines intelligent approaches that continuously analyze data flows generated by Supervisory Control And Data Acquisition (SCADA) systems, which monitor contemporary power grid infrastructures. However, cybersecurity threats and security mechanisms cannot be analyzed and tested on actual systems, and thus testbed simulators are necessary to assess vulnerabilities and evaluate the infrastructure resilience against cyberattacks. This report suggests an agent-based model to simulate SCADA- like cyber-components behaviour when facing cyber-infection in order to experiment and test intelligent mitigation mechanisms. 

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  • 5.
    Atif, Yacine
    et al.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Kharrazi, Sogol
    National Road Transport Research Institute, Linköping, Sweden.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Andler, Sten F.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Internet of Things data analytics for parking availability prediction and guidance2020In: European transactions on telecommunications, ISSN 1124-318X, E-ISSN 2161-3915, Vol. 31, article id e3862Article in journal (Refereed)
    Abstract [en]

    Cutting-edge sensors and devices are increasingly deployed within urban areas to make-up the fabric of transmission control protocol/internet protocol con- nectivity driven by Internet of Things (IoT). This immersion into physical urban environments creates new data streams, which could be exploited to deliver novel cloud-based services. Connected vehicles and road-infrastructure data are leveraged in this article to build applications that alleviate notorious parking and induced traffic-congestion issues. To optimize the utility of parking lots, our proposed SmartPark algorithm employs a discrete Markov-chain model to demystify the future state of a parking lot, by the time a vehicle is expected to reach it. The algorithm features three modular sections. First, a search pro- cess is triggered to identify the expected arrival-time periods to all parking lots in the targeted central business district (CBD) area. This process utilizes smart-pole data streams reporting congestion rates across parking area junc- tions. Then, a predictive analytics phase uses consolidated historical data about past parking dynamics to infer a state-transition matrix, showing the transfor- mation of available spots in a parking lot over short periods of time. Finally, this matrix is projected against similar future seasonal periods to figure out the actual vacancy-expectation of a lot. The performance evaluation over an actual busy CBD area in Stockholm (Sweden) shows increased scalability capa- bilities, when further parking resources are made available, compared to a baseline case algorithm. Using standard urban-mobility simulation packages, the traffic-congestion-aware SmartPark is also shown to minimize the journey duration to the selected parking lot while maximizing the chances to find an available spot at the selected lot.

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  • 6.
    Chaparadza, Ranganai
    et al.
    ETSI AFI & IPv6Forum.
    Ben Meriem, Tayeb
    Orange, AFI.
    Radier, Benoit
    Orange, AFI.
    Szott, Szymon
    AGH University , AFI.
    Wodczak, Michal
    IT Department of Poznan University of Economics, AFI.
    Prakash, Arun
    FOKUS, AFI.
    Ding, Jianguo
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Soulhi, Said
    Ericsson, AFI.
    Mihailovic, Andrej
    KCL, AFI.
    Implementation Guide for the ETSI AFI GANA Model: a Standardized Reference Model for Autonomic Networking, Cognitive Networking and Self-Management2013In: Proceedings of 2013 IEEE Globecom Workshops, IEEE Computer Society, 2013, p. 935-940Conference paper (Refereed)
    Abstract [en]

    This paper describes an Implementation Guide for an emerging standard for autonomic management &control of networks and services, namely the ETSI AFI GANA Reference Model for Autonomic Networking, Cognitive Networking and Self-Management (an emerging standard from ETSI). The implementation guide also takes into consideration the impact of emerging paradigms such as SDN and Virtualization. This is because as the standardized Reference Model has been published, it becomes important to provide an associated Implementation Guide that can be followed in implementing autonomic management & control in network architectures.

  • 7.
    Chaparadza, Ranganai
    et al.
    ETSI AFI & IPv6Forum.
    Ben Meriem, Tayeb
    Orange, AFI.
    Radier, Benoit
    Orange, AFI.
    Szott, Szymon
    AGH University, AFI.
    Wodczak, Michal
    IT Department of Poznan University of Economics, AFI.
    Prakash, Arun
    FOKUS, AFI.
    Ding, Jianguo
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Soulhi, Said
    Ericsson, AFI.
    Mihailovic, Andrej
    KCL, AFI.
    SDN Enablers in the ETSI AFI GANA Reference Model for Autonomic Management & Control (emerging standard), and Virtualization Impact2013In: Proceedings of 2013 IEEE Globecom Workshops, IEEE Computer Society, 2013, p. 818-823Conference paper (Refereed)
    Abstract [en]

    This standardization oriented paper describes the SDN (Software-Driven Networking) Enablers in the ETSI AFI GANA Reference Model for Autonomic Management & Control (an emerging standard from ETSI), and impact of Virtualization. This is because in this study we see that Autonomic Management & Control and SDN (Software-Driven Networking) share the same objective of enabling programmable, manageable, dynamically self-adaptable and cost-effective networks and services. SDN enablers in the AFI GANA Model are: (1) Modularization of Logically centralized Control Software (the GANA Network Level DEs in the GANA Knowledge Plane) and Reference Points Definitions; (2) Primitives for Programmability at various layers; (3) Use of Runtime Executable Behavioral Models to complement the use of Policy-Control and dynamic policies; (4) The role and value the GANA MBTS (Model Based Translation Service) brings in SDN; (5) The role and value the GANA ONIX (Overlay Network for Information eXchange) brings in SDN; (6) Interworking GANA Knowledge Plane Decision Elements and SDN Controllers; (7) GANA “Decision-Making-Elements” logics as “software” that can be loaded into nodes and network (enabling “software-empowered networks”). The study is important because it is now becoming critical to study and explore the relationships between Autonomic Management & Control and SDN paradigms, as well as Virtualization, identify complementarities between the paradigms and close the gaps by unifying SDN concepts and associated frameworks with the emerging ETSI AFI GANA Reference Model standard for Autonomic Networking, Cognitive Networking and Self-Management, a hybrid model enabling to combine both centralized and distributed control.

  • 8.
    Chaparadza, Ranganai
    et al.
    IPv6Forum / ETSI AFI.
    Ben Meriem, Tayeb
    Orange / ETSI AFI.
    Strassner, John
    Huawei / TMF ZOOM.
    Radier, Benoit
    Orange / ETSI NTECH/AFI.
    Soulhi, Said
    Ericsson / ETSI/NTECH AFI.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Yan, Zhiwei
    CNNIC / Chinese Academy of Sciences.
    Industry Harmonization for Unified Standards on Autonomic Management & Control (AMC) of Networks and Services, SDN and NFV2014In: 2014 IEEE Globecom Workshops (GC Wkshps), IEEE conference proceedings, 2014, p. 155-160Conference paper (Refereed)
  • 9.
    Chaparadza, Ranganai
    et al.
    IPv6Forum & ETSI AFI, Berlin, Germany.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Djenouri, Djamel
    CERIST Research Center, Algiers, Algeria.
    Preface of the 6th IEEE International Workshop on Management of Emerging Networks and Services (IEEE Globecom MENS 2014)2014In: 2014 IEEE Globecom Workshops (GC Wkshps), IEEE conference proceedings, 2014, p. 150-154Conference paper (Refereed)
  • 10.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Intrusion Detection, Prevention, and Response System (IDPRS) for Cyber-Physical Systems (CPSs)2015In: Securing Cyber Physical Systems / [ed] Al-Sakib Khan Pathan, Boca Raton, US: Taylor & Francis Group, 2015, p. 371-392Chapter in book (Refereed)
    Abstract [en]

    Cyber-physical systems (CPSs) are integrated physical, engineered, andsocial systems whose operations are monitored, coordinated, controlled, and integratedby a computing and communication core. Due to the dynamic structure ofCPSs, the security measurements are often complex. Given this fact, the objectiveof this chapter is to present the intrusion detection, prevention, and response system(IDPRS) for such a dynamic environment.

  • 11.
    Ding, Jianguo
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten F.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    CPS-based Threat Modeling for Critical Infrastructure Protection2017In: Performance Evaluation Review, ISSN 0163-5999, E-ISSN 1557-9484, Vol. 45, no 2, p. 129-132Article in journal (Refereed)
    Abstract [en]

    Cyber-Physical Systems (CPSs) are augmenting traditionalCritical Infrastructures (CIs) with data-rich operations. Thisintegration creates complex interdependencies that exposeCIs and their components to new threats. A systematicapproach to threat modeling is necessary to assess CIs’ vulnerabilityto cyber, physical, or social attacks. We suggest anew threat modeling approach to systematically synthesizeknowledge about the safety management of complex CIs andsituational awareness that helps understanding the nature ofa threat and its potential cascading-effects implications.

  • 12.
    Ding, Jianguo
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Chaparadza, Ranganai
    IPv6 Forum, ETSI-AFI , Berlin , Germany.
    Network Management2016In: Encyclopedia of Information Systems and Technology / [ed] Phillip A. Laplante, CRC Press, 2016, p. 881-899Chapter in book (Refereed)
  • 13.
    Ding, Jianguo
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Mathiason, Gunnar
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten F.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Towards Threat Modeling for CPS-based Critical Infrastructure Protection2015In: Proceedings of the International Emergency Management Society (TIEMS), 22nd TIEMS Annual Conference: Evolving threats and vulnerability landscape: new challenges for the emergency management / [ed] Snjezana Knezic & Meen Poudyal Chhetri, Brussels: TIEMS, The International Emergency Management Society , 2015, Vol. 22Conference paper (Refereed)
    Abstract [en]

    With the evolution of modern Critical Infrastructures (CI), more Cyber-Physical systems are integrated into the traditional CIs. This makes the CIs a multidimensional complex system, which is characterized by integrating cyber-physical systems into CI sectors (e.g., transportation, energy or food & agriculture). This integration creates complex interdependencies and dynamics among the system and its components. We suggest using a model with a multi-dimensional operational specification to allow detection of operational threats. Embedded (and distributed) information systems are critical parts of the CI where disruption can lead to serious consequences. Embedded information system protection is therefore crucial. As there are many different stakeholders of a CI, comprehensive protection must be viewed as a cross-sector activity to identify and monitor the critical elements, evaluate and determine the threat, and eliminate potential vulnerabilities in the CI. A systematic approach to threat modeling is necessary to support the CI threat and vulnerability assessment. We suggest a Threat Graph Model (TGM) to systematically model the complex CIs. Such modeling is expected to help the understanding of the nature of a threat and its impact on throughout the system. In order to handle threat cascading, the model must capture local vulnerabilities as well as how a threat might propagate to other components. The model can be used for improving the resilience of the CI by encouraging a design that enhances the system's ability to predict threats and mitigate their damages. This paper surveys and investigates the various threats and current approaches to threat modeling of CI. We suggest integrating both a vulnerability model and an attack model, and we incorporate the interdependencies within CI cross CI sectors. Finally, we present a multi-dimensional threat modeling approach for critical infrastructure protection.

  • 14.
    Ding, Jianguo
    et al.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. Department of Computer Science, Blekinge Institute of Technology, Karlskrona, Sweden.
    Naserinia, Vahid
    University of Skövde, School of Informatics.
    Blockchain for future renewable energy2022In: Decentralized Frameworks for Future Power Systems: Operation, Planning and Control Perspectives / [ed] Mohsen Parsa Moghaddam; Reza Zamani; Hassan Haes Alhelou; Pierluigi Siano, Academic Press, 2022, p. 129-146Chapter in book (Refereed)
    Abstract [en]

    To better optimize and control the renewable energy system and its integration with traditional grid systems and other energy systems, corresponding technologies are needed to meet its growing practical application requirements: decentralized management and control, support for decentralized decision-making, fine-grained and timely data sharing, maintain data and business privacy, support fast and low-cost electricity market transactions, maintain the security and reliability of system operation data, and prevent malicious cyberattacks. Blockchain is based on core technologies such as distributed ledgers, asymmetric encryption, consensus mechanisms, and smart contracts and has some excellent features such as decentralization, openness, independence, security, and anonymity. These characteristics seem to meet the technical requirements of future renewable energy systems partially. This chapter will systematically review how blockchain technology can potentially solve the challenges with decentralized solutions for future renewable energy systems and show a guideline to implement blockchain-based corresponding applications for future renewable energy. 

  • 15.
    Ding, Jianguo
    et al.
    Blekinge Tekniska Högskola, Institutionen för datavetenskap.
    Tadesse Aklilu, Yohannes
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Blockchain for Smart Grid Operations, Control and Management2022Report (Other academic)
    Abstract [en]

    A comprehensive overview of blockchain-based smart grid management, control, and operation solutions. The report compares with related reviews and highlights the challenges in management, control, and operation for a blockchain-based smart grid, as well as future research directions in five categories: collaboration between actors, data analytics and management, control of network imbalances, decentralization of network management and operation, security and privacy.

    The report reviews how blockchain technology can potentially solve the challenges of decentralized solutions for future renewable energy systems. As a result, several applications of blockchain for renewable energy are discussed, such as electric vehicles, decentralized P2P energy transactions, carbon certification and trading, physical information security, energy transfer, Energy-to-X, and the Internet of Energy.

    A guideline for the implementation of blockchain to corresponding applications for future renewable energy is also presented in this report. This includes the different blockchain system architectures, the data flow from the power grid processed and recorded, the choice of the appropriate consensus, and the different blockchain frameworks.

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  • 16.
    Jeusfeld, Manfred A.
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jiang, Yuning
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Haglund, Daniel
    Combitech AB.
    Brax, Christoffer
    Combitech AB.
    Taxonomy of Events and Components in the Power Grid: Technical description for work packages 3.1 and 3.2 of the ELVIRA Project2018Report (Other academic)
    Abstract [en]

    This document reports a technical description of ELVIRA project results obtained as part of Work-package 3.1&3.2 entitled “Taxonomy of Critical Infrastructure (Taxonomy of events + Taxonomy of CI component and relationship)”. ELVIRA project is a collaboration between researchers in School of IT at University of Skövde and Combitech Technical Consulting Company in Sweden, with the aim to design, develop and test a testbed simulator for critical infrastructures cybersecurity.

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    HS-IIT-TR-18-001
  • 17.
    Jiang, Yuning
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Agent Based Testbed Design for Cyber Vulnerability Assessment in Smart-Grids2018Conference paper (Other academic)
    Abstract [en]

    Smart grid employs Information and Communication Technology (ICT) infrastructure and network connectivity to optimize efficiency and deliver new functionalities. This evolution is associated with an increased risk for cybersecurity threats that may hamper smart grid operations. Power utility providers need tools for assessing risk of prevailing cyberthreats over ICT infrastructures. The need for frameworks to guide the development of these tools is essential to define and reveal vulnerability analysis indicators. We propose a data-driven approach for designing testbeds to allow the simulation of cyberattacks in order to evaluate the vulnerability and the impact of cyber threat attacks. The proposed framework uses data reported from multiple smart grid components at different smart grid architecture layers, including physical, control, and cyber layers. The multi-agent based framework proposed in this paper would analyze the conglomeration of these data reports to assert malicious attacks.

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  • 18.
    Jiang, Yuning
    et al.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Cyber-Physical Systems Security Based on A Cross-Linked and Correlated Vulnerability Database2019In: Critical Information Infrastructures Security: 14th International Conference, CRITIS 2019, Linköping, Sweden, September 23–25, 2019, Revised Selected Papers / [ed] Simin Nadjm-Tehrani, Springer, 2019, Vol. 11777, p. 71-82Chapter in book (Refereed)
    Abstract [en]

    Recent advances in data analytics prompt dynamic datadriven vulnerability assessments whereby data contained from vulnerabilityalert repositories as well as from Cyber-physical System (CPS) layer networks and standardised enumerations. Yet, current vulnerability assessment processes are mostly conducted manually. However, the huge volume of scanned data requires substantial information processing and analytical reasoning, which could not be satisfied considering the imprecision of manual vulnerability analysis. In this paper, we propose to employ a cross-linked and correlated database to collect, extract, filter and visualise vulnerability data across multiple existing repositories, whereby CPS vulnerability information is inferred. Based on our locally-updated database, we provide an in-depth case study on gathered CPS vulnerability data, to explore the trends of CPS vulnerability. In doing so, we aim to support a higher level of automation in vulnerability awareness and back risk-analysis exercises in critical infrastructures (CIs) protection.

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  • 19.
    Jiang, Yuning
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Data Fusion Framework for Cyber Vulnerability Assessment in Smart Grid2018Other (Other academic)
    Abstract [en]

    Smart grid adopts ICT to enhance power-delivery management. However, these advanced technologies also introduce an increasing amount of cyber threats. Cyber threats occur because of vulnerabilities throughout smart-grid layers. Each layer is distinguished by typical data flows. For example, power-data stream flows along the physical layer; command data are pushed to and pulled from sensor-control devices, such as RTUs and PLCs. Vulnerabilities expose these data flows to cyber threat via communication networks, such as local control network, vendor network, corporate network and the wider internet. Thus, these data could be used to analyse vulnerabilities against cyber threats. After data collection, data analysis and modelling techniques would be used for vulnerability assessment.

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  • 20.
    Jiang, Yuning
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Multi-Level Vulnerability Modeling of Cyber-Physical Systems2018Conference paper (Refereed)
    Abstract [en]

    Vulnerability is defined as ”weakness of an asset or control that can be exploited by a threat” according to ISO/IEC 27000:2009, and it is a vital cyber-security issue to protect cyber-physical systems (CPSs) employed in a range of critical infrastructures (CIs). However, how to quantify both individual and system vulnerability are still not clear. In our proposed poster, we suggest a new procedure to evaluate CPS vulnerability. We reveal a vulnerability-tree model to support the evaluation of CPS-wide vulnerability index, driven by a hierarchy of vulnerability-scenarios resulting synchronously or propagated by tandem vulnerabilities throughout CPS architecture, and that could be exploited by threat agents. Multiple vulnerabilities are linked by boolean operations at each level of the tree. Lower-level vulnerabilities in the tree structure can be exploited by threat agents in order to reach parent vulnerabilities with increasing CPS criticality impacts. At the asset-level, we suggest a novel fuzzy-logic based valuation of vulnerability along standard metrics. Both the procedure and fuzzy-based approach are discussed and illustrated through SCADA-based smart power-grid system as a case study in the poster, with our goal to streamline the process of vulnerability computation at both asset and CPS levels.

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    fulltext
  • 21.
    Jiang, Yuning
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Wang, Wei
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    A Semantic Framework With Humans in the Loop for Vulnerability-Assessment in Cyber-Physical Production Systems2020In: Risks and Security of Internet and Systems: 14th International Conference, CRiSIS 2019, Hammamet, Tunisia, October 29–31, 2019, Proceedings / [ed] Slim Kallel, Frédéric Cuppens, Nora Cuppens-Boulahia, Ahmed Hadj Kacem, Springer, 2020, Vol. 12026, p. 128-143Conference paper (Refereed)
    Abstract [en]

    Criticalmanufacturingprocessesinsmartnetworkedsystems such as Cyber-Physical Production Systems (CPPSs) typically require guaranteed quality-of-service performances, which is supported by cyber- security management. Currently, most existing vulnerability-assessment techniques mostly rely on only the security department due to limited communication between di↵erent working groups. This poses a limitation to the security management of CPPSs, as malicious operations may use new exploits that occur between successive analysis milestones or across departmental managerial boundaries. Thus, it is important to study and analyse CPPS networks’ security, in terms of vulnerability analysis that accounts for humans in the production process loop, to prevent potential threats to infiltrate through cross-layer gaps and to reduce the magnitude of their impact. We propose a semantic framework that supports the col- laboration between di↵erent actors in the production process, to improve situation awareness for cyberthreats prevention. Stakeholders with dif- ferent expertise are contributing to vulnerability assessment, which can be further combined with attack-scenario analysis to provide more prac- tical analysis. In doing so, we show through a case study evaluation how our proposed framework leverages crucial relationships between vulner- abilities, threats and attacks, in order to narrow further the risk-window induced by discoverable vulnerabilities.

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    fulltext
  • 22.
    Jiang, Yuning
    et al.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Jeusfeld, Manfred
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Andler, Sten
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Brax, Christoffer
    Combitech, Sweden.
    Haglund, Daniel
    Combitech, Sweden.
    Complex Dependencies Analysis: Technical Description of Complex Dependencies in Critical Infrastructures, i.e. Smart Grids. Work Package 2.1 of the ELVIRA Project2018Report (Other academic)
    Abstract [en]

    This document reports a technical description of ELVIRA project results obtained as part of Work-package 2.1 entitled “Complex Dependencies Analysis”. In this technical report, we review attempts in recent researches where connections are regarded as influencing factors to  IT systems monitoring critical infrastructure, based on which potential dependencies and resulting disturbances are identified and categorized. Each kind of dependence has been discussed based on our own entity based model. Among those dependencies, logical and functional connections have been analysed with more details on modelling and simulation techniques.

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    ELVIRA_2.1-HS-IIT-TR-18-003.Complex-Dependencies-Analysis
  • 23.
    Jiang, Yuning
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Atif, Yacine
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Brax, Christoffer
    Combitech AB, Skövde, Sweden.
    Nero, Eva
    Combitech AB, Skövde, Sweden.
    A Language and Repository for Cyber Security of Smart Grids2018In: 2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC 2018) / [ed] Selmin Nurcan, Pontus Johnson, Los Alamitos, CA: IEEE, 2018, p. 164-170Conference paper (Refereed)
    Abstract [en]

    Power grids form the central critical infrastructure in all developed economies. Disruptions of power supply can cause major effects on the economy and the livelihood of citizens. At the same time, power grids are being targeted by sophisticated cyber attacks. To counter these threats, we propose a domain-specific language and a repository to represent power grids and related IT components that control the power grid. We apply our tool to a standard example used in the literature to assess its expressiveness.

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    fulltext
  • 24.
    Jiang, Yuning
    et al.
    University of Skövde, Informatics Research Environment. University of Skövde, School of Informatics.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Evaluating the Data Inconsistency of Open-Source Vulnerability Repositories2021In: ARES 2021: The 16th International Conference on Availability, Reliability and Security, Association for Computing Machinery (ACM), 2021, p. 1-10, article id 86Conference paper (Refereed)
    Abstract [en]

    Modern security practices promote quantitative methods to provide prioritisation insights and support predictive analysis, which is supported by open-source cybersecurity databases such as the Common Vulnerabilities and Exposures (CVE), the National Vulnerability Database (NVD), CERT, and vendor websites. These public repositories provide a way to standardise and share up-to-date vulnerability information, with the purpose to enhance cybersecurity awareness. However, data quality issues of these vulnerability repositories may lead to incorrect prioritisation and misemployment of resources. In this paper, we aim to empirically analyse the data quality impact of vulnerability repositories for actual information technology (IT) and operating technology (OT) systems, especially on data inconsistency. Our case study shows that data inconsistency may misdirect investment of cybersecurity resources. Instead, correlated vulnerability repositories and trustworthiness data verification bring substantial benefits for vulnerability management. 

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    fulltext
  • 25.
    Jiang, Yuning
    et al.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. Nanyang Technological University, Singapore.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Ding, Jianguo
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Sandahl, Elin
    Norgald AB, Göteborg, Sweden.
    Model-Based Cybersecurity Analysis: Extending Enterprise Modeling to Critical Infrastructure Cybersecurity2023In: Business & Information Systems Engineering, ISSN 2363-7005, E-ISSN 1867-0202, Vol. 65, no 6, p. 643-676Article in journal (Refereed)
    Abstract [en]

    Critical infrastructure (CIs) such as power grids link a plethora of physical components from many different vendors to the software systems that control them. These systems are constantly threatened by sophisticated cyber attacks. The need to improve the cybersecurity of such CIs, through holistic system modeling and vulnerability analysis, cannot be overstated. This is challenging since a CI incorporates complex data from multiple interconnected physical and computation systems. Meanwhile, exploiting vulnerabilities in different information technology (IT) and operational technology (OT) systems leads to various cascading effects due to interconnections between systems. The paper investigates the use of a comprehensive taxonomy to model such interconnections and the implied dependencies within complex CIs, bridging the knowledge gap between IT security and OT security. The complexity of CI dependence analysis is harnessed by partitioning complicated dependencies into cyber and cyber-physical functional dependencies. These defined functional dependencies further support cascade modeling for vulnerability severity assessment and identification of critical components in a complex system. On top of the proposed taxonomy, the paper further suggests power-grid reference models that enhance the reproducibility and applicability of the proposed method. The methodology followed was design science research (DSR) to support the designing and validation of the proposed artifacts. More specifically, the structural, functional adequacy, compatibility, and coverage characteristics of the proposed artifacts are evaluated through a three-fold validation (two case studies and expert interviews). The first study uses two instantiated power-grid models extracted from existing architectures and frameworks like the IEC 62351 series. The second study involves a real-world municipal power grid.

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  • 26.
    Modig, Dennis
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Performance impacts on container based virtualization in virtualized residential gateways2016In: Proceedings of 39th International Conference on Telecommunications and Signal Processing (TSP), 2016, IEEE, 2016, p. 27-32Conference paper (Refereed)
    Abstract [en]

    Over the past years the use of digital devices has increased and home networks continue to grow in size and complexity. By the use of virtualized residential gateways advanced functionality can be moved away from the home by extending the customers edge network to the Internet Service Provider (ISP) and thereby decrease the administrative burden for the home user. By employing edge computing and cloud applications at the operator by virtualizing residential gateways instead of using physical devices creates new challenges. This paper is looking at how the choice of virtualization technology impacts performance by investigating operating system level virtualization in contrast to full virtualization for use in virtualized residential gateways. Results show that container based virtualization uses fewer resources in terms of disk, memory, and processor in virtualized residential gateways.

  • 27.
    Tadesse, Yohannes
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Ding, Jianguo
    Department of Computer Science, Blekinge Institute of Technology, Karlskrona, Sweden.
    Survey on blockchain for smart grid management, control, and operation2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 1, article id 193Article, review/survey (Refereed)
    Abstract [en]

    Power generation, distribution, transmission, and consumption face ongoing challenges such as smart grid management, control, and operation, resulting from high energy demand, the diversity of energy sources, and environmental or regulatory issues. This paper provides a comprehensive overview of blockchain-based solutions for smart grid management, control, and operations. We systematically summarize existing work on the use and implementation of blockchain technology in various smart grid domains. The paper compares related reviews and highlights the challenges in the management, control, and operation for a blockchain-based smart grid as well as future research directions in the five categories: collaboration among stakeholders; data analysis and data manage-ment; control of grid imbalances; decentralization of grid management and operations; and security and privacy. All these aspects have not been covered in previous reviews. 

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  • 28.
    Ye, Xiaozhen
    et al.
    School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China.
    Backlund, Per
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Ning, Huansheng
    School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China.
    Fidelity in Simulation-based Serious Games2020In: IEEE Transactions on Learning Technologies, ISSN 1939-1382, E-ISSN 1939-1382, Vol. 13, no 2, p. 340-353Article in journal (Refereed)
    Abstract [en]

    The extensive use of Simulation-based Serious Games (SSGs) has made a revolution in educational techniques. As a potentially significant feature for SSG design and evaluation, the term fidelity (the similarity between an SSG and its real reference) emerges and attracts increasing attention. The study of fidelity not only benefits the design, development, and analysis of an SSG with the consideration of improving the learning effect but also contributes to the investment reduction of an SSG. However, the term fidelity is used inconsistently in current literature. The introduction of new technologies (e.g. virtual reality) and the blend of multiform SSGs also facilitate the extension of fidelity with new connotations. All lead to confusing concepts and vague measure metrics. Besides, the relationship between fidelity and learning effect is still uncertain. A new vision and a comprehensive conceptual framework of fidelity for more general applications are in need. In this paper, further exploration and discussion of these issues in relation to fidelity of SSGs are presented through a systematic review. A general conceptual framework considering both aspects of the SSG system itself and the learners is developed and applied to analyze fidelity in SSGs. Based on that, a discussion on fidelity related issues of SSG design and development is presented.

  • 29.
    Ye, Xiaozhen
    et al.
    School of Computer and Communication Engineering, University of Science and Technology Beijing, China / Shunde Graduate School, University of Science and Technology Beijing, China.
    Ning, Huansheng
    School of Computer and Communication Engineering, University of Science and Technology Beijing, China / Shunde Graduate School, University of Science and Technology Beijing, China.
    Backlund, Per
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Ding, Jianguo
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Flow Experience Detection and Analysis for Game Users by Wearable-Devices-Based Physiological Responses Capture2021In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 8, no 3, p. 1373-1387Article in journal (Refereed)
    Abstract [en]

    Relevant research has shown the potential to understand the game user experience (GUX) more accurately and reliably by measuring the user’s psychophysiological responses. However, the current studies are still very scarce and limited in scope and depth. Besides, the low-detection accuracy and the common use of the professional physiological signal apparatus make it difficult to be applied in practice. This article analyzes the GUX, particularly flow experience, based on users’ physiological responses, including the galvanic skin response (GSR) and heart rate (HR) signals, captured by low-cost wearable devices. Based on the collected data sets regarding two test games and the mixed data set, several classification models were constructed to detect the flow state automatically. Hereinto, two strategies were proposed and applied to improve classification performance. The results demonstrated that the flow experience of game users could be effectively classified from other experiences. The best accuracies of two-way classification and three-way classification under the support of the proposed strategies were over 90% and 80%, respectively. Specifically, the comparison test with the existing results showed that Strategy1 could significantly reduce the negative interference of individual differences in physiological signals and improve the classification accuracy. In addition, the results of the mixed data set identified the potential of a general classification model of flow experience.

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