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    Managing threats by the use of visualisation techniques

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    Authors
    Viduto, Valentina
    Maple, Carsten
    Huang, Wei
    Issue Date
    2011
    Subjects
    onion skin model
    OSM
    visualisation techniques
    risk management
    attack graphs
    attack trees
    network hardening
    network threats
    risk assessment
    network attacks
    threat identification
    decision making
    vulnerable nodes
    vulnerability
    network security
    attack scenarios
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    Abstract
    Identification of threats in networked systems is one of the important risk management processes that should be followed in order to be aware of all risks. In general, risk assessment guidelines for threat analysis propose to use historical organisation's data, thus, novel and unheard threats often are skipped from an analysis. In this paper, we propose a novel onion skin model (OSM) which consists of visualisation techniques, such as attack graphs, often applied for qualitative and quantitative risk assessment analyses. The model can be used to facilitate in threat identification and decision-making process by focusing on attack scenarios that illustrate vulnerable nodes, threats and shortest attack paths to the attacker's goal. The model can be used as part of risk management practices to improve security awareness through different attack scenarios and manage all system risks.
    Citation
    Viduto, V., Maple, C., Huang, W. (2011) 'Managing threats by the use of visualisation techniques' International Journal of Space-Based and Situated Computing 1 (2/3):204-212
    Publisher
    Inderscience
    Journal
    International Journal of Space-Based and Situated Computing
    URI
    http://hdl.handle.net/10547/250947
    DOI
    10.1504/IJSSC.2011.040347
    Additional Links
    http://www.inderscience.com/link.php?id=40347
    Type
    Article
    Language
    en
    ISSN
    2044-4893
    2044-4907
    ae974a485f413a2113503eed53cd6c53
    10.1504/IJSSC.2011.040347
    Scopus Count
    Collections
    Centre for Wireless Research (CWR)

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