Incremental fuzzy decision tree-based network forensic system

Authors:
Zaiqiang Liu;Dengguo Feng
Affiliations:
State Key Laboratory of Information Security, Institute of Software, Chinese Academy of Sciences, Beijing, China;State Key Laboratory of Information Security, Institute of Software, Chinese Academy of Sciences, Beijing, China
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
Year:
2005

Citing 5
Cited 1

Fuzzy set theory—and its applications (3rd ed.)

Fuzzy set theory—and its applications (3rd ed.)
Mining in a data-flow environment: experience in network intrusion detection

KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Incremental Fuzzy Decision Trees

KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
Data mining approaches for intrusion detection

SSYM'98 Proceedings of the 7th conference on USENIX Security Symposium - Volume 7
Fuzzy decision trees: issues and methods

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Network forensic frameworks: Survey and research challenges

Digital Investigation: The International Journal of Digital Forensics & Incident Response

Quantified Score

Hi-index	0.00

Visualization

Abstract

Network forensic plays an important role in the modern network environment for computer security, but it has become a time-consuming and daunting task due to the sheer amount of data involved. This paper proposes a new method for constructing incremental fuzzy decision trees based on network service type to reduce the human intervention and time-cost, and to improve the comprehensibility of the results. At the end of paper, we discuss the performance of the forensic system and present the result of experiments.