Automated Insider Threat Detection System Using User and Role-Based Profile Assessment
- Submitting institution
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University of Oxford
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1954
- Type
- D - Journal article
- DOI
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10.1109/JSYST.2015.2438442
- Title of journal
- IEEE SYSTEMS JOURNAL
- Article number
- 2
- First page
- 503
- Volume
- 11
- Issue
- 2
- ISSN
- 1932-8184
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
-
-
- Citation count
- 34
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper, building on an IEEE Security and Privacy conference version, pulls together the research in a three-year project on insider-threat detection sponsored by the National Cyber Security Programme, later continued with funding from the security services. The work has gained traction internationally, and other researchers have adopted the approach based on statistical (PCA) methods (see e.g. work at MIST�17 https://doi.org/10.1145/3139923.3139928). There was close collaboration, in particular, with the Insider Threat team at CMU/SEI/CERT, with mutual validation of results.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -