Abstract
With the increase in volume, heterogeneity and uncertainty in data, conventional analytics approaches for monitoring users behavior in organisations are no longer sufficient for the effective and reliable detection of malicious activities. This motivates the need for introducing additional analysis techniques. This paper introduces an intelligent fusion method based on fuzzy aggregation functions typically utilized in multi-criteria decision making. The proposed method, which can be integrated with analytics systems, undertakes temporal and multi-criteria fusion processes on pre-analyzed data, to enhance effective monitoring and decision-making. An application to a prominent area of research in the cyber-security domain, the insider threat problem, is shown to validate the usefulness of our method
Original language | English |
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Title of host publication | 2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS 2017) |
Subtitle of host publication | Proceedings of a meeting held 27-30 June 2017, Otsu, Japan |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 329-334 |
Number of pages | 6 |
ISBN (Electronic) | 9781509049172 |
ISBN (Print) | 9781509049189 |
DOIs | |
Publication status | Published - Sept 2017 |
Event | Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems - Otsu, Japan, Otsu, Japan Duration: 26 Jun 2017 → 30 Jun 2017 |
Conference
Conference | Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems |
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Abbreviated title | IFSA-SCIS 2017 |
Country/Territory | Japan |
City | Otsu |
Period | 26/06/17 → 30/06/17 |