Computational approaches to finding and measuring inconsistency in arbitrary knowledge bases
- Submitting institution
-
Queen's University of Belfast
- Unit of assessment
- 12 - Engineering
- Output identifier
- 124233537
- Type
- D - Journal article
- DOI
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10.1016/j.ijar.2014.06.003
- Title of journal
- International Journal of Approximate Reasoning
- Article number
- -
- First page
- 1659
- Volume
- 55
- Issue
- 8
- ISSN
- 0888-613X
- Open access status
- Out of scope for open access requirements
- Month of publication
- November
- Year of publication
- 2014
- 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
-
2
- Research group(s)
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C - Electrical and Electronic
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A novel optimized transformation approach to computing minimal inconsistent subsets in knowledge bases is described, enabling the first computationally tractable solution to this problem. Formal verification of security tools is critical. Our approach has enabled us to develop a tool for inconsistency handling that can formally verify security rule-sets used in network intrusion detection and access control. The proposed approach is based on a formal mathematical treatment using propositional logic. Furthermore, the first rigorous experimental evaluation of an inconsistency tool using a large dataset of randomly generated knowledge bases is performed.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -