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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.
    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.
    Andler, Sten F.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Yuning, Jiang
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    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. 

  • 2.
    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.

  • 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.
    Lindström, Birgitta
    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
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    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. 

  • 4.
    Brax, Christoffer
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Anomaly Detection in the Surveillance Domain2011Doctoral thesis, monograph (Other academic)
    Abstract [en]

    In the post September 11 era, the demand for security has increased in virtually all parts of the society. The need for increased security originates from the emergence of new threats which differ from the traditional ones in such a way that they cannot be easily defined and are sometimes unknown or hidden in the “noise” of daily life.

    When the threats are known and definable, methods based on situation recognition can be used find them. However, when the threats are hard or impossible to define, other approaches must be used. One such approach is data-driven anomaly detection, where a model of normalcy is built and used to find anomalies, that is, things that do not fit the normal model. Anomaly detection has been identified as one of many enabling technologies for increasing security in the society.

    In this thesis, the problem of how to detect anomalies in the surveillance domain is studied. This is done by a characterisation of the surveillance domain and a literature review that identifies a number of weaknesses in previous anomaly detection methods used in the surveillance domain. Examples of identified weaknesses include: the handling of contextual information, the inclusion of expert knowledge and the handling of joint attributes. Based on the findings from this study, a new anomaly detection method is proposed. The proposed method is evaluated with respect to detection performance and computational cost on a number datasets, recorded from real-world sensors, in different application areas of the surveillance domain. Additionally, the method is also compared to two other commonly used anomaly detection methods. Finally, the method is evaluated on a dataset with anomalies developed together with maritime subject matter experts. The conclusion of the thesis is that the proposed method has a number of strengths compared to previous methods and is suitable foruse in operative maritime command and control systems.

  • 5.
    Brax, Christoffer
    et al.
    Training Systems and Information Fusion, Business Area Electronic Defence Systems, Saab AB, Skövde, Sweden.
    Dahlbom, Anders
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    A Study of Anomaly Detection in Data from Urban Sensor Networks2012In: Modeling Decisions for Artificial Intelligence: 9th International Conference, MDAI 2012, Girona, Catalonia, Spain, November 21-23, 2012. Proceedings / [ed] Vicenç Torra, Yasuo Narukawa, Beatriz López, Mateu Villaret, Springer Berlin/Heidelberg, 2012, p. 185-196Conference paper (Refereed)
    Abstract [en]

    In many sensor systems used in urban environments, the amount of data produced can be vast. To aid operators of such systems, high-level information fusion can be used for automatically analyzing the surveillance information. In this paper an anomaly detection approach for finding areas with traffic patterns that deviate from what is considered normal is evaluated. The use of such approaches could help operators in identifying areas with an increased risk for ambushes  or improvised explosive devices (IEDs).

  • 6.
    Brax, Christoffer
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Karlsson, Alexander
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten F.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Johansson, Ronnie
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Niklasson, Lars
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Evaluating Precise and Imprecise State-Based Anomaly Detectors for Maritime Surveillance2010In: Proceedings of the 13th International Conference on Information Fusion, IEEE conference proceedings, 2010, p. Article number 5711997-Conference paper (Refereed)
    Abstract [en]

    We extend the State-Based Anomaly Detection approach by introducing precise and imprecise anomaly detectors using the Bayesian and credal combination operators, where evidences over time are combined into a joint evidence. We use imprecision in order to represent the sensitivity of the classification regarding an object being  normal or anomalous. We evaluate the detectors on a real-world maritime dataset containing recorded AIS data and show that the anomaly detectors outperform   previously proposed detectors based on Gaussian mixture models and kernel density estimators. We also show that our introduced anomaly detectors perform slightly better than the State-Based Anomaly Detection approach with a sliding window.

  • 7.
    Brax, Christoffer
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Niklasson, Lars
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    An approach for increased supply chain security by using automatic detection of anomalous vehicle behavior2009In: CD-ROM Proceedings of the 6th International Conference on Modeling Decisions for Artificial Intelligence (MDAI 2009), 2009, p. 165-176Conference paper (Refereed)
    Abstract [en]

    In recent years, the development of low-cost GPS transceivers has made it possible to equip all trucks in a fleet with equipment for automatically reporting the status of the trucks to a fleet management system. The downside is that the huge amount of information that is gathered must be evaluated in real-time by an operator. We propose the use of a data-driven anomaly detection algorithm that learns "normal" vehicle behaviour and detects anomalous behaviour such as smuggling, accidents and hijacking, The algorithm is evaluated on real-world data from trucks and commuters equipped with GPS transceivers. The results give initial support to the claim that anomaly detection based on statistical learning can be used to support human descision making. This ability can increase supply chain security by alerting an operator on anomalous vehicle behaviour.

  • 8.
    Brax, Christoffer
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Niklasson, Lars
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Enhanced situational Awareness in the Maritime Domain: An Agent-based Approach for Situation Management2009In: Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing: Proceedings of SPIE Defense, Security, and Sensing 2009 / [ed] Stephen Mott, John F Buford, Gabriel Jakobson, SPIE Press , 2009, p. Aticle ID 735203-Conference paper (Refereed)
    Abstract [en]

    Maritime Domain Awareness is important for both civilian and military applications. An important part of MDA is detection of unusual vessel activities such as piracy, smuggling, poaching, collisions, etc. Today's interconnected sensorsystems provide us with huge amounts of information over large geographical areas which can make the operators reach their cognitive capacity and start to miss important events. We propose and agent-based situation management system that automatically analyse sensor information to detect unusual activity and anomalies. The system combines knowledge-based detection with data-driven anomaly detection. The system is evaluated using information from both radar and AIS sensors.

  • 9.
    Brax, Christoffer
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Niklasson, Lars
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Laxhammar, Rikard
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    An ensemble approach for increased anomaly detection performance in video surveillance data2009In: Proceedings of the 12th International Conference on Information Fusion (FUSION 2009), Seattle, Washington, USA, 6–9 July 2009, IEEE conference proceedings, 2009, p. 694-701Conference paper (Refereed)
    Abstract [en]

    The increased societal need for surveillance and the decrease in cost of sensors have led to a number of new challenges. The problem is not to collect data but to use it effectively for decision support. Manual interpretation of huge amounts of data in real-time is not feasible; the operator of a surveillance system needs support to analyze and understand all incoming data. In this paper an approach to intelligent video surveillance is presented, with emphasis on finding behavioural anomalies. Two different anomaly detection methods are compared and combined. The results show that it is possible to best increase the total detection performance by combining two different anomaly detectors rather than employing them independently.

     

  • 10.
    Brax, Christoffer
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Niklasson, Lars
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Smedberg, Martin
    Saab Microwave Systems, Saab AB, Gothenburg, Sweden.
    Finding behavioural anomalies in public areas using video surveillance data2008In: Proceedings of the 11th International Conference on Information Fusion, IEEE conference proceedings, 2008, p. 1655-1662Conference paper (Refereed)
    Abstract [en]

     In this paper we propose an approach forvdetecting anomalies in data from visual surveillancevsensors. The approach includes creating a structure for representing data, building “normal models” by filling the structure with data for the situation at hand, and finally detecting deviations in the data. The approach allows detections based on the incorporation of a priori knowledge about the situation and on data-driven analysis. The main advantages with the approach compared to earlier work is the low computational requirements, iterative update of normal models and a high explainability of found anomalies. The proposed approach is evaluated off-line using real-world data and the results support that the approach could be used to detect anomalies in real-time applications.

     

  • 11.
    Fooladvandi, Farzad
    et al.
    Saab Microwave Systems, Training systems and Information Fusion Skövde, Sweden.
    Brax, Christoffer
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. Saab Microwave Systems.
    Gustavsson, Per
    Saab Microwave Systems, Training systems and Information Fusion Skövde, Sweden.
    Fredin, Mikael
    Saab Microwave Systems, Training systems and Information Fusion Skövde, Sweden.
    Signature-based activity detection based on Bayesian networks acquired from expert knowledge2009In: Proceedings of the 12th International Conference on Information Fusion (FUSION 2009), ISIF , 2009, p. 436-443Conference paper (Refereed)
    Abstract [en]

     

    The maritime industry is experiencing one of its longest and fastest periods of growth. Hence, the global maritime surveillance capacity is in a great need of growth as well. The detection of vessel activity is an important objective of the civil security domain. Detecting vessel activity may become problematic if audit data is uncertain. This paper aims to investigate if Bayesian networks acquired from expert knowledge can detect activities with a signature-based detection approach. For this, a maritime pilot-boat scenario has been identified with a domain expert. Each of the scenario’s activities has been divided up into signatures where each signature relates to a specific Bayesian network information node. The signatures were implemented to find evidences for the Bayesian network information nodes. AIS-data with real world observations have been used for testing, which have shown that it is possible to detect the maritime pilot-boat scenario based on the taken approach.

     

  • 12.
    Gustavsson, Per M.
    et al.
    University of Skövde, School of Humanities and Informatics. Modeling and Simulation, Sensor and Information Networks, Ericsson Microwave Systems AB, Skövde, Sweden / De Montfort University, Leicester, UK.
    Björk, Åsa
    Modeling and Simulation, Sensor and Information Networks, Ericsson Microwave Systems AB, Skövde, Sweden.
    Brax, Christoffer
    Modeling and Simulation, Sensor and Information Networks, Ericsson Microwave Systems AB, Skövde, Sweden.
    Planstedt, Tomas
    Modeling and Simulation, Sensor and Information Networks, Ericsson Microwave Systems AB, Skövde, Sweden.
    Towards Service Oriented Simulations2004In: Fall Simulation Interoperability Workshop 2004: FallSIW 04, 2004, p. 219-229Conference paper (Other academic)
    Abstract [en]

    In the effort to provide simulation support to the future Network Based Defence (NBD)1 that are currently being applied by the Swedish Armed Forces (SwAF), the authors opinion is that simulation should be treated as any other services and use the same architectural requirements addressed in the SwAF Enterprise Architecture (FMA)2 and in subsidiary documents.

    The choice so far for simulation is the High Level Architecture (HLA). During the author’s participation in ongoing work supporting NBD, questions have gradually been raised if HLA is the simulation path to walk. In the Core Enterprise Services (CES) and FMA Services IT-Kernel, core services are specified and HLA do address a lot of non-simulation specific services giving unwanted redundancy. However, the services already defined may with some enhancements deliver the same services addressed within CES and FMA Services IT-Kernel. Furthermore, HLA also comes with the Federation Development and Execution Process (FEDEP) that introduce process methodology to build HLA federations. Basically FEDEP is a software development process for distributed systems. The Next Generation HLA could be more than just a simulation standard if it utilizes the FMA ideas and avoids the green HLA elephant3.

    In this paper the authors present the ongoing work, as it stands today, with Service Oriented Simulations, that is an outlook for simulation using the architectural structuring, services, components and infrastructures concepts evolving in FMA and with the Global Information Grid (GIG) Enterprise Services (GES) in mind. The focus is to identify simulation services that encapsulate the core features of simulation. Thereby reducing redundancy in methodology and service as well as enabling interoperable simulation support for the whole system lifecycle – Acquisition, Development, Training, Planning, In-the-Field decision support, System removal – within NBD, entailing that the architecture for simulation is uniform regardless of its application and giving end-users the capability to focus on what to simulate instead of how to simulate.

  • 13.
    Gustavsson, Per M.
    et al.
    Research and Concept Development, M&S and Information Fusion, Ericsson, Ericsson, Skövde, Sweden.
    Brax, Christoffer
    University of Skövde, School of Humanities and Informatics.
    An Agent Architecture for Multi-Hypothesis Intention Simulation: An Ontology Driven Interoperabilty Architecture2006In: The 10th World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI 2006), International Institute of Informatics and Systemics, 2006, Vol. 4, p. 77-82Conference paper (Other academic)
  • 14.
    Jiang, Yuning
    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.
    Atif, Yacine
    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.
    Andler, Sten
    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.
    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.

  • 15.
    Niklasson, Lars
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Riveiro, Maria
    University of Skövde, The Informatics Research Centre. University of Skövde, Skövde Artificial Intelligence Lab (SAIL). University of Skövde, School of Humanities and Informatics.
    Johansson, Fredrik
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. University of Skövde, Skövde Artificial Intelligence Lab (SAIL).
    Dahlbom, Anders
    University of Skövde, The Informatics Research Centre. University of Skövde, School of Humanities and Informatics. University of Skövde, Skövde Artificial Intelligence Lab (SAIL).
    Falkman, Göran
    University of Skövde, The Informatics Research Centre. University of Skövde, School of Humanities and Informatics. University of Skövde, Skövde Artificial Intelligence Lab (SAIL).
    Ziemke, Tom
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Brax, Christoffer
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. University of Skövde, Skövde Artificial Intelligence Lab (SAIL). Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Kronhamn, Thomas
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Smedberg, Martin
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Warston, Håkan
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Gustavsson, Per M.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. University of Skövde, Skövde Artificial Intelligence Lab (SAIL). Saab Microwave Systems, Skövde, Sweden.
    A Unified Situation Analysis Model for Human and Machine Situation Awareness2007In: INFORMATIK 2007: Informatik trifft Logistik: Band 2: Beiträge der 37. Jahrestagung der Gesellschaft für Informatik e.V. (GI) 24. - 27. September 2007 in Bremen / [ed] Otthein Herzog, Karl-Heinz Rödiger, Marc Ronthaler, Rainer Koschke, Bonn: Gesellschaft für Informatik , 2007, p. 105-109Conference paper (Refereed)
  • 16.
    Niklasson, Lars
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Riveiro, Maria
    University of Skövde, The Informatics Research Centre. University of Skövde, School of Humanities and Informatics.
    Johansson, Fredrik
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. University of Skövde, Skövde Artificial Intelligence Lab (SAIL).
    Dahlbom, Anders
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. University of Skövde, Skövde Artificial Intelligence Lab (SAIL).
    Falkman, Göran
    University of Skövde, The Informatics Research Centre. University of Skövde, Skövde Artificial Intelligence Lab (SAIL). University of Skövde, School of Humanities and Informatics.
    Ziemke, Tom
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Brax, Christoffer
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Kronhamn, Thomas
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Smedberg, Martin
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Warston, Håkan
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Gustavsson, Per M.
    Product Development, Saab Microwave Systems, Gothenburg, Sweden.
    Extending the scope of Situation Analysis2008In: Proceedings of the 11th International Conference on Information Fusion (FUSION 2008), Cologne, Germany, June 30–July 3, 2008, IEEE Press, 2008, p. 454-461Conference paper (Refereed)
    Abstract [en]

    The use of technology to assist human decision making has been around for quite some time now. In the literature, models of both technological and human aspects of this support can be identified. However, we argue that there is a need for a unified model which synthesizes and extends existing models. In this paper, we give two perspectives on situation analysis: a technological perspective and a human perspective. These two perspectives are merged into a unified situation analysis model for semi-automatic, automatic and manual decision support (SAM)2. The unified model can be applied to decision support systems with any degree of automation. Moreover, an extension of the proposed model is developed which can be used for discussing important concepts such as common operational picture and common situation awareness.

  • 17.
    Tiberg, Jesper
    et al.
    Vehco (www.vehco.com), Gothenburg, Sweden / JPB Solutions ( www.jpbs.se), Sweden.
    Brax, Christoffer
    University of Skövde, School of Humanities and Informatics. M&S and Information Fusion Security Solutions Ericsson, Skövde, Sweden.
    Gustavsson, Per M.
    University of Skövde, School of Humanities and Informatics.
    Towards Hypothesis Evaluation in Command and Control Systems2006In: SAIS 2006: The 23rd Annual Workshop of the Swedish Artificial Intelligence Society, Umeå: Swedish Artificial Intelligence Society - SAIS , 2006, p. 97-102Conference paper (Other academic)
    Abstract [en]

    This work focus on situation prediction in data fusion systems. A hypothesis evaluation algorithm based on artificial neural networks is introduced. It is evaluated and compared to an algorithm based on Bayesian networks which is commonly used. It is also compared to a simple "dummy" algorithm. For the tests, a computer based model of the environment, including protected objects and enemy objects, is implemented. The model handles the navigation of the enemy objects and situational data is extracted from the environment and provided for the hypothesis evaluation algorithms. It was the belief of the author that ANNs would be suitable for hypothesis evaluation if a suitable data representation of the environment were used. The representation requirements include pre processing of the situational data to eliminate the need for variable input size to the algorithm. This because ANNs poorly handles this; the whole network have to be retrained each time the amount of input data changes. The results show that ANNs performed best of the three and hence seems to be suitable for hypothesis evaluation.

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