Density-Based Spam Detector

• YOSHIDA Kenichi

  Graduate School of Business Science, University of Tsukuba

• ADACHI Fuminori

  Institute of Scientific and Industrial Research, Osaka University

• WASHIO Takashi

  Institute of Scientific and Industrial Research, Osaka University

• MOTODA Hiroshi

  Institute of Scientific and Industrial Research, Osaka University

• HOMMA Teruaki

  KDDI Corporation

• NAKASHIMA Akihiro

  KDDI Corporation

• FUJIKAWA Hiromitsu

  KDDI R&D Laboratories Inc.

• YAMAZAKI Katsuyuki

  KDDI R&D Laboratories Inc.

抄録

The volume of mass unsolicited electronic mail, often known as spam, has recently increased enormously and has become a serious threat not only to the Internet but also to society. This paper proposes a new spam detection method which uses document space density information. Although the proposed method requires extensive e-mail traffic to acquire the necessary information, it can achieve perfect detection (i.e., both recall and precision is 100%) under practical conditions. A direct-mapped cache method contributes to the handling of over 13,000 e-mail messages per second. Experimental results, which were conducted using over 50 million actual e-mail messages, are also reported in this paper.

収録刊行物

• IEICE transactions on information and systems

  IEICE transactions on information and systems 87 (12), 2678-2688, 2004-12-01

  一般社団法人電子情報通信学会

キーワード

• spam
• unsupervised learning
• document space density
• direct-mapped cache

詳細情報

• CRID: 1573668927255984896
• NII論文ID: 110003213877
• NII書誌ID: AA10826272
• ISSN: 09168532
• 本文言語コード: en
• データソース種別:
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