A technique to reduce false positives of network IDS with machine learning (Japanese)

In: Transactions of the Information Processing Society of Japan   ;  45 ,  8  ;  2105-2112  ;  2004
  • ISSN:
  • Article (Journal)  /  Print

How to get this document?

Recently, network-based IDS (network-based intrusion detection systems), which always observes the packets flowing in the networks, has become the focus of the public attention with increasing security incident. However, network-based IDS frequently mistakes attacks. Especially, IDS generates many false positives, that are bogus alerts caused by mistakes normal events with attacks. Many false positives cause problems for administrators, who have to distinguish real attacks with false positives in IDS log. In this paper, we proposed a technique to detect false positives in IDS log by learning patterns of false positives with machine learning. And we implemented and evaluated the proposal system, and proved effectiveness of our proposal.

Table of contents – Volume 45, Issue 8

Show all volumes and issues

The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.

Proposal of an iris identification scheme hiding iris codes
Ota, H. / Kiyomoto, S. / Tanaka, T. | 2004
Design of security architecture for beyond 3G mobile terminals
Kiyomoto, S. / Tanaka, T. / Yoshida, M. / Kuroda, M. | 2004
On anonymity metrics for practical anonymous communication protocols
Kitazawa, S. / Soshi, M. / Miyaji, A. | 2004
A study for some experiences of the operation of highly interactive decoy system
Shibuya, Y. / Koike, H. / Takada, T. / Yasumura, M. / Ishii, T. | 2004
Routing information based packet filtering for IP spoofing prevention
Nakano, M. / Matsumoto, T. | 2004
Regression test selection based on intermediate code for virtual machines
Koju, T. / Takada, S. / Doi, N. | 2004
Generation of character animation holding a tool with its both hands by using three 6DOF trackers
Kawasaki, R. / Kitamura, Y. / Kishino, F. | 2004
A technique to reduce false positives of network IDS with machine learning
Ohya, H. / Miyaji, R. / Kawaguchi, N. / Shigeno, H. / Okada, K. | 2004