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VISAD: an interactive and visual analytical tool for the detection of behavioural anomalieis in maritime traffic data
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. University of Skövde, Skövde Artificial Intelligence Lab (SAIL).ORCID iD: 0000-0003-2900-9335
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre. University of Skövde, Skövde Artificial Intelligence Lab (SAIL).ORCID iD: 0000-0001-8884-2154
University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.ORCID iD: 0000-0001-6883-2450
Saab Microwave Systems AB (Sweden).
2009 (English)In: Visual Analytics for Homeland Defense and Security: Proceedings of SPIE Defense, Security, and Sensing 2009 / [ed] William J. Tolone, William Ribarsky, SPIE - International Society for Optical Engineering, 2009, Article ID 734607- p.Conference paper, (Refereed)
Abstract [en]

Monitoring the surveillance of large sea areas normally involves the analysis of huge quantities of heterogeneous data from multiple sources (radars, cameras, automatic identification systems, reports, etc.). The rapid identification of anomalous behavior or any threat activity in the data is an important objective for enabling homeland security. While it is worth acknowledging that many existing mining applications support identification of anomalous behavior, autonomous anomaly detection systems are rarely used in the real world. There are two main reasons: (1) the detection of anomalous behavior is normally not a well-defined and structured problem and therefore, automatic data mining approaches do not work well and (2) the difficulties that these systems have regarding the representation and employment of the prior knowledge that the users bring to their tasks. In order to overcome these limitations, we believe that human involvement in the entire discovery process is crucial.

Using a visual analytics process model as a framework, we present VISAD: an interactive, visual knowledge discovery tool for supporting the detection and identification of anomalous behavior in maritime traffic data. VISAD supports the insertion of human expert knowledge in (1) the preparation of the system, (2) the establishment of the normal picture and (3) in the actual detection of rare events. For each of these three modules, VISAD implements different layers of data mining, visualization and interaction techniques. Thus, the detection procedure becomes transparent to the user, which increases his/her confidence and trust in the system and overall, in the whole discovery process.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2009. Article ID 734607- p.
Series
Proceedings of SPIE - The International Society for Optical Engineering, ISSN 0277-786X ; 7346
Keyword [en]
anomaly detection, visual analytics, interactive visualization, data mining, maritime sensor data
National Category
Computer and Information Science
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-3235DOI: 10.1117/12.817819Scopus ID: 2-s2.0-79959428639ISBN: 9780819476128 OAI: oai:DiVA.org:his-3235DiVA: diva2:225897
Conference
Visual analytics for homeland defense and security : 14 April 2009, Orlando, Florida, United States
Available from: 2009-06-29 Created: 2009-06-29 Last updated: 2014-09-22Bibliographically approved

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