Detecting hostile accesses through incremental subspace clustering

M. Narahashi, E. Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We propose an incremental subspace clustering method for flexibly detecting hostile accesses to a Web site. Typical log data for Web accesses are huge, contain irrelevant information, and exhibit dynamic characteristics. We overcome these difficulties through data squashing, subspace clustering, and an incremental algorithm. We have improved, by modifying its data squashing functionality, our subspace clustering method SUBCCOM so that it can exploit previous results. Experimental evaluation confirms superiority of our I-SUBCCOM in terms of precision, recall, and computation time.

Original languageEnglish
Title of host publicationProceedings - IEEE/WIC International Conference on Web Intelligence, WI 2003
EditorsJiming Liu, Nick Cercone, Matthias Klusch, Chunnian Liu, Ning Zhong
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages337-343
Number of pages7
ISBN (Electronic)0769519326, 9780769519326
DOIs
Publication statusPublished - 2003
Externally publishedYes
EventIEEE/WIC International Conference on Web Intelligence, WI 2003 - Halifax, Canada
Duration: Oct 13 2003Oct 17 2003

Publication series

NameProceedings - IEEE/WIC International Conference on Web Intelligence, WI 2003

Other

OtherIEEE/WIC International Conference on Web Intelligence, WI 2003
Country/TerritoryCanada
CityHalifax
Period10/13/0310/17/03

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Information Systems
  • Computer Networks and Communications
  • Human-Computer Interaction
  • Information Systems and Management

Fingerprint

Dive into the research topics of 'Detecting hostile accesses through incremental subspace clustering'. Together they form a unique fingerprint.

Cite this