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  • 1.
    Al Mamun, Abdullah
    et al.
    Division of Software Engineering Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
    Berger, Christian
    Division of Software Engineering Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
    Hansson, Jörgen
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Explicating, Understanding and Managing Technical Debt from Self-Driving Miniature Car Projects2014Inngår i: Proceedings 2014 6th IEEE International Workshop on Managing Technical Debt: MTD 2014, Los Alamitos, CA: IEEE Computer Society, 2014, s. 11-18Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Technical debt refers to various weaknesses in the design or implementation of a system resulting from trade-offs during software development usually for a quick release. Accumulating such debt over time without reducing it can seriously hamper the reusability and maintainability of the software. The aim of this study is to understand the state of the technical debt in the development of self-driving miniature cars so that proper actions can be planned to reduce the debt to have more reusable and maintainable software. A case study on a selected feature from two self-driving miniature car development projects is performed to assess the technical debt. Additionally, an interview study is conducted involving the developers to relate the findings of the case study with the possible root causes. The result of the study indicates that "the lack of knowledge" is not the primary reason for the accumulation of technical debt from the selected code smells. The root causes are rather in factors like time pressure followed by issues related to software/hardware integration and incomplete refactoring as well as reuse of legacy, third party, or open source code.

  • 2.
    Atif, Yacine
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Ding, Jianguo
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Lindström, Birgitta
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Jeusfeld, Manfred
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Andler, Sten F.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Yuning, Jiang
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Brax, Christoffer
    CombiTech AB, Skövde, Sweden.
    Gustavsson, Per M.
    CombiTech AB, Skövde, Sweden.
    Cyber-Threat Intelligence Architecture for Smart-Grid Critical Infrastructures Protection2017Konferansepaper (Fagfellevurdert)
    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. 

    Fulltekst (pdf)
    fulltext
  • 3.
    Jiang, Yuning
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Dynamic and Automatic Vulnerability Assessment for Cyber-Physical System2019Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    Assessing vulnerabilities supports analytics-based decision-making processes to protect Critical Infrastructures (CIs), in order to focus on specific risks rising from threat-exploitability with varying degrees of impact-severity. The notion of risk remains elusive, as evidenced by the increasing investigations on CIs security operations centres (SOCs) where analysts employ various detection, assessment, and defence mechanisms to monitor security events. Normally, SOCs involve advances of multiple automated security tools such as network vulnerability scanners and Common Vulnerability Scoring System (CVSS), combined with analysis of data contained and produced by cyber-physical system (CPS) as well as alarms retrieved from vulnerability repositories such as Common Vulnerability Exposure (CVE). The security operators need further to forecast the match between these vulnerabilities and the state of intricate CIs layer networks, while prioritising patching investments using vulnerability-scoring mechanisms. This process shows the central role of security operators in SOCs and their need for support to keep pace with dynamically evolving vulnerability-alert repositories. Recent advances in data analytics also prompt dynamic data-driven vulnerability assessments whereby data contained and produced by CPS include hidden traces of vulnerability fingerprints. However, the huge volume of scanned data requires high capability of information processing and analytical reasoning, which could not be satisfied considering the imprecise nature of manual vulnerability assessment.

    A knowledge-base system that consolidates both sides into empirical rules appears to be missing, yet it promises to offer a suitable level of decision-support. In our research, we propose a dynamic and automated vulnerability-assessment approach. The proposed streamlined approach employs computational intelligence techniques to analyse data retrieved from vulnerability-alert repositories and CPS layer networks within an innovative accurate and automatic scoring system, away from traditional manual and highly subjective mechanisms. Our approach suggests to substitute offline, costly, error-prone and pure subjective vulnerability assessment processes with an automatic, accurate and data-evidenced approach, to improve situation awareness and to support security decision making. In doing so, we investigate judicious computational-intelligence techniques such as fuzzy-logic, machine learning and data mining, applied to vulnerability assessment problems.

    Fulltekst (png)
    fulltext
  • 4.
    Jiang, Yuning
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Atif, Yacine
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Ding, Jianguo
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Multi-Level Vulnerability Modeling of Cyber-Physical Systems2018Konferansepaper (Fagfellevurdert)
    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.

    Fulltekst (pdf)
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  • 5.
    Jiang, Yuning
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Atif, Yacine
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Ding, Jianguo
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Wang, Wei
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system.
    A Semantic Framework With Humans in the Loop for Vulnerability-Assessment in Cyber-Physical Production Systems2020Inngår i: 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, s. 128-143Konferansepaper (Fagfellevurdert)
    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.

  • 6.
    Jiang, Yuning
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Ding, Jianguo
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Atif, Yacine
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Jeusfeld, Manfred
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Andler, Sten
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Lindström, Birgitta
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    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 Project2018Rapport (Annet vitenskapelig)
    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.

    Fulltekst (pdf)
    ELVIRA_2.1-HS-IIT-TR-18-003.Complex-Dependencies-Analysis
  • 7.
    Laurell, Isak
    et al.
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap.
    Sjöholm, Linus
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap.
    System för insamling av väderdata2017Independent thesis Basic level (degree of Bachelor), 20 poäng / 30 hpOppgave
    Abstract [sv]

    På försvarets materielverk (FMV) i Karlsborg utförs prover av militära vapensystem. Ofta när prov genomförs samlas också väderdata in för att veta om yttre faktorer kan påverka en träffbild. Insamling av väderdata är en manuell process som FMV önskar att automatisera. Målet är att skapa ett system med hjälp av en befintlig vädersensor som kan visa väderparametrar i realtid på en skärm samt spara dem vid rätt tillfälle på ett flyttbart media. Vid utveckling av system för insamling av väderdata ska det väljas ut lämplig hårdvara där även mjukvaran ska formas. Den teoretiska referensramen och litteraturstudierna utgjorde en bra grund för hela projektet genom att få en förståelse om alla de delar som måste tas hänsyn till. FMV har som krav att hårdvaran ska vara baserad på en integrerad krets. Det innebär kortfattat att det inte finns något operativsystem utan att det består endast av en källkod. Den befintliga vädersensorn som ska användas kommunicerar via seriell kommunikation. Det gjordes också ett val mellan två utvecklingsmodeller där en av dem senare ska användas som ett hjälpmedel för utvecklingsprocessen av hela systemet. Den utvecklingsmodell som var mest lämplig för projektet var V-modellen. Genom att använda V-modellen togs det fram en bra struktur för hur arbetet skulle läggas upp gällande planering, verkställande och testning. Med en detaljerad planering underlättade det verkställandet genom att det fanns en tydlig bild av vad som skulle göras. Den noga planeringen gjorde att fel och brister i systemet vid testerna var få. En nyckelfaktor för utvecklingsprocessen var också att ha ett bra samarbete med FMV:s personal vilket gjorde att utvecklingen följde deras vision om systemet. När utvecklingsprocessen och arbetet med V-modellen var genomfört var också ett system för insamling av väderdata framtaget och godkänt av FMV. Systemet generar en minskad hantering av data eftersom det utför det arbete som tidigare har varit manuellt. Det generar också stabilare mätvärden eftersom tidpunkten för loggningen blir mer exakt än tidigare.

    Fulltekst (pdf)
    fulltext
  • 8.
    Liebel, Grischa
    et al.
    Software Engineering Division, Chalmers / University of Gothenburg, Sweden.
    Marko, Nadja
    Virtual Vehicle Research Center, Graz, Austria.
    Tichy, Matthias
    Software Engineering Division, Chalmers / University of Gothenburg, Sweden.
    Leitner, Andrea
    Virtual Vehicle Research Center, Graz, Austria.
    Hansson, Jörgen
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Assessing the state-of-practice of model-based engineering in the embedded systems domain2014Inngår i: Model-Driven Engineering Languages and Systems: 17th International Conference, MODELS 2014, Valencia, Spain, September 28 – October 3, 2014. Proceedings / [ed] Juergen Dingel, Wolfram Schulte, Isidro Ramos, Silvia Abrahão, Emilio Insfran, Springer, 2014, s. 166-182Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Abstract Model-Based Engineering (MBE) aims at increasing the effectiveness of engineering by using models as key artifacts in the development process. While empirical studies on the use and the effects of MBE in industry exist, there is only little work targeting the embedded systems domain. We contribute to the body of knowledge with a study on the use and the assessment of MBE in that particular domain. We collected quantitative data from 112 subjects, mostly professionals working with MBE, with the goal to assess the ...

  • 9.
    Mellin, Jonas
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Andler, Sten F.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    The effect of optimizing engine control on fuel consumption and roll amplitude in ocean-going vessels: An experimental study2015Rapport (Annet vitenskapelig)
    Abstract [en]

    We use data-generated models based on data from experiments of an ocean-going vessel to study the effect of optimizing fuel consumption. The optimization is an add-on module to the existing diesel-engine fuel-injection control built by Q-TAGG R&D AB. The work is mainly a validation of knowledge-based models based on a priori knowledge from physics. The results from a simulation-based analysis of the predictive models built on data agree with the results based on knowledge-based models in a companion study. This indicates that the optimization algorithm saves fuel. We also address specific problems of adapting data to existing machine learning methods. It turns out that we can simplify the problem by ignoring the auto-correlative effects in the time series by employing low-pass filters and resampling techniques. Thereby we can use mature and robust classification techniques with less requirements on the data to demonstrate that fuel is saved compared to the full-fledged time series analysis techniques which are harder to use. The trade-off is the accuracy of the result, that is, it is hard to tell exactly how much fuel is saved. In essence, however, this process can be automated due to its simplicity. 

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