oru.sePublikationer
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Anomaly detection in the surveillance domain
Örebro University, School of Science and Technology.
2011 (English)Doctoral 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.

Place, publisher, year, edition, pages
Örebro: Örebro universitet , 2011. , 208 p.
Series
Örebro Studies in Technology, ISSN 1650-8580 ; 50
Keyword [en]
Anomaly Detection, Information Fusion, Visual Surveillance, Maritime Domain Awareness
National Category
Natural Sciences Computer and Information Science
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-16373ISBN: 978-91-7668-810-6 (print)OAI: oai:DiVA.org:oru-16373DiVA: diva2:431243
Public defence
2011-09-19, Insikten, Kanikegränd 3A, Högskolan i Skövde, Skövde, 13:15
Opponent
Supervisors
Note
Christoffer Brax forskar också vid högskolan i Skövde, Informatics Research Centre / Christoffer Brax also does research at the University of Skövde, Informatics Research CentreAvailable from: 2011-07-18 Created: 2011-07-18 Last updated: 2011-10-27Bibliographically approved

Open Access in DiVA

fulltext(17378 kB)1995 downloads
File information
File name FULLTEXT01.pdfFile size 17378 kBChecksum SHA-512
9161fcf82a66420967f5001182836d90d7de532c5099304f94d3bf1e8d3b3dca25dce985a79b87bcdd2569941722c58a4d4fbd2d3c2ab1b72c6c2b54261b134e
Type fulltextMimetype application/pdf
omslag(1577 kB)83 downloads
File information
File name COVER01.pdfFile size 1577 kBChecksum SHA-512
72ea210126db0c806c3ea4ae27a6414920c0e08fb77f7c5ce95bf139deaa7b46fb8301b67f7cc6786ebd0391fc76ec313378d3e3c2677eae499fac6ba3381a0b
Type coverMimetype application/pdf
omslag(2906 kB)29 downloads
File information
File name COVER02.pdfFile size 2906 kBChecksum SHA-512
5bde30205812eccdb5c85b8efd00ecb5c46eea30c01e001aba47e2b2bd2389b7919fcb32ca021a4351b9a35e060280568518d4f399c4b6185d1219f4253a941a
Type coverMimetype application/pdf
spikblad(89 kB)20 downloads
File information
File name SPIKBLAD01.pdfFile size 89 kBChecksum SHA-512
4631b8ca2f04137b69c67553aad59366b2837d240ba4c74f80b9cac601bd3dbeff0704287ec6322bc343fe69b40b4245b002079d34097a479a9a028958873b3b
Type spikbladMimetype application/pdf

By organisation
School of Science and Technology
Natural SciencesComputer and Information Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 1995 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 2238 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf