Fuzzy Logic Model for Digital Forensics: A Trade-off between Accuracy, Complexity and Interpretability

被引:0
作者
Shalaginov, Andrii [1 ]
机构
[1] Norwegian Univ Sci & Technol, Ctr Cyber & Informat Secur, Trondheim, Norway
来源
PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE | 2017年
关键词
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Cyber Crime Investigation is challenged by large and complex data as a key factor of emerging Information and Communication Technologies. The size, the velocity, the variety and the complexity of the data have become so high that data mining approaches are no more efficient since they cannot deal with Big Data. As a result, it can be infeasible to represent specific evidences found in such data in a Court of Law in a human-perceivable manner. Moreover, majority of computational methods result in complex and hardly explainable models. However, Soft Computing, a computing with words, can be beneficial in such case. In particular, hybrid Neuro-Fuzzy is capable of learning understandable and precise fuzzy rule-based model. This paper presents novel improvements of NF architecture and corresponding results.
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页码:5207 / 5208
页数:2
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