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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yow Tzu Lim Pau Chen Cheng Clark, J.A. Rohatgi, P. |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Comput. Sci., Univ. of York, York (Yow Tzu Lim) |
| Abstract | In the early days a policy was a set of simple rules with a clear intuitive motivation that could be formalised to good effect. However the world is now much more complex. Subtle risk decisions may often need to be made and people are not always adept at expressing rationale for what they do. Previous research has demonstrated that Genetic Programming can be used to infer statements of policies from examples of decisions made [1]. This allows a policy that may not formally have been documented to be discovered automatically, or an underlying set of requirements to be extracted by interpreting user decisions to posed ldquowhat ifrdquo scenarios. This study compares the performance of three different approaches in using genetic programming to infer security policies from decision examples made, namely symbolic regression, IF-THEN rules inference and fuzzy membership functions inference. The fuzzy membership functions inference approach is found to have the best performance in terms of accuracy. Also, the fuzzification and de-fuzzification methods are found to be strongly correlated; incompatibility between them can have strong negative impact to the performance. |
| Starting Page | 1792 |
| Ending Page | 1800 |
| File Size | 291688 |
| Page Count | 9 |
| File Format | |
| ISBN | 9781424418220 |
| DOI | 10.1109/CEC.2008.4631032 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-06-01 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Security Training Genetic programming Sensitivity Decision making Adaptation model Testing |
| Content Type | Text |
| Resource Type | Article |
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