Automated Expert System Knowledge Base Development Method for Information Security Risk Analysis
| Autor: | Donatas Vitkus, Nikolaj Goranin, Žilvinas Steckevičius, Antanas Čenys, Diana Kalibatienė |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer Networks and Communications
Computer science 020209 energy Rule Interchange Format 02 engineering and technology 010501 environmental sciences Ontology (information science) computer.software_genre 01 natural sciences JESS Information security management 0202 electrical engineering electronic engineering information engineering ontology RDF information security risk analysis 0105 earth and related environmental sciences RIF business.industry transformation Principal (computer security) Information security computer.file_format Expert system Computer Science Applications expert sys-tem Computational Theory and Mathematics Risk analysis (engineering) Knowledge base knowledge base business computer |
| Zdroj: | INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL. 14:743 |
| ISSN: | 1841-9844 1841-9836 |
| DOI: | 10.15837/ijccc.2019.6.3668 |
| Popis: | Information security risk analysis is a compulsory requirement both from the side of regulating documents and information security management decision making process. Some researchers propose using expert systems (ES) for process automation, but this approach requires the creation of a high-quality knowledge base. A knowledge base can be formed both from expert knowledge or information collected from other sources of information. The problem of such approach is that experts or good quality knowledge sources are expensive. In this paper we propose the problem solution by providing an automated ES knowledge base development method. The method proposed is novel since unlike other methods it does not integrate ontology directly but utilizes automated transformation of existing information security ontology elements into ES rules: The Web Ontology Rule Language (OWL RL) subset of ontology is segregated into Resource Description Framework (RDF) triplets, that are transformed into Rule Interchange Format (RIF); RIF rules are converted into Java Expert System Shell (JESS) knowledge base rules. The experiments performed have shown the principal method applicability. The created knowledge base was later verified by performing comparative risk analysis in a sample company. |
| Databáze: | OpenAIRE |
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