首页> 外文OA文献 >Towards eradication of SPAM: A study on intelligent adaptive SPAM filters
【2h】

Towards eradication of SPAM: A study on intelligent adaptive SPAM filters

机译:致力于消除垃圾邮件:智能自适应垃圾邮件过滤器的研究

摘要

As the massive increase of electronic mail (email) usage continues, SPAM (unsolicited bulk email), has continued to grow because it is a very inexpensive method of advertising. These unwanted emails can cause a serious problem by filling up the email inbox and thereby leaving no space for legitimate emails to pass through. Currently the only defense against SPAM is the use of SPAM filters. A novel SPAM filter GetEmail5 along with the design rationale, is described in this thesis. To test the efficacy of GetEmail5 SPAM filter, an experimental setup was created and a commercial bulk email program was used to send SPAM and non-SPAM emails to test the new SPAM filter. ududGetEmail5's efficiency and ability to detect SPAM was compared against two highly ranked commercial SPAM filters on different sets of emails, these included all SPAM, non-SPAM, and mixed emails, also text and HTML emails.ududThe results showed the superiority of GetEmail5 compared to the two commercial SPAM filters in detecting SPAM emails and reducing the user's involvement in categorizing the incoming emails. ududThis thesis demonstrates the design rationale for GetEmail5 and also its greater effectiveness in comparison with the commercial SPAM filters tested.
机译:随着电子邮件(电子邮件)使用量的大量增加,SPAM(不请自来的批量电子邮件)继续增长,因为它是一种非常便宜的广告方法。这些多余的电子邮件可能会由于填满电子邮件收件箱而导致严重的问题,从而使合法电子邮件无法通过。当前,唯一针对SPAM的防御措施就是使用SPAM筛选器。本文介绍了一种新颖的垃圾邮件过滤器GetEmail5及其设计原理。为了测试GetEmail5 SPAM过滤器的有效性,创建了一个实验性设置,并使用了一个商业批量电子邮件程序来发送SPAM和非Spam电子邮件,以测试新的SPAM过滤器。 ud udGetEmail5的效率和检测垃圾邮件的能力与在不同电子邮件集上的两个高度排名商业SPAM过滤器进行了比较,其中包括所有垃圾邮件,非垃圾邮件和混合电子邮件,还包括文本和HTML电子邮件。 ud ud结果显示与两个商业SPAM过滤器相比,GetEmail5的优势在于可检测SPAM电子邮件并减少用户对传入电子邮件进行分类的参与。 ud ud本文证明了GetEmail5的设计原理,并且与经过测试的商用SPAM过滤器相比,它的有效性更高。

著录项

  • 作者

    Hassan Tarek;

  • 作者单位
  • 年度 2006
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号