Evaluating spam detection techniques using ranking algorithm in email network at Hanoi University

Authors

  • Vu Minh Tuan Hanoi University
  • Tran Quang Anh Faculty of Information Technology - Hanoi University
  • Ha Quang Minh Faculty of Information Technology - Hanoi University

DOI:

https://doi.org/10.15625/1813-9663/30/3/3253

Keywords:

Spam detection, email network, clustering, PageRank algorithm, user ranking

Abstract

In this paper, four spam-filtering approaches based on user ranking in the mail networks: Clustering, Extended Clustering Coefficient, PageRank Algorithm and Weighted PageRank Algorithm are analyzed. We also propose a couple of fully worked-out datasets from the email network of Hanoi University against which the experimental comparisons with the respect to the accuracy of email user ranking and spam filtering are conducted. The results indicate that PageRank Algorithm and Extended Clustering Coefficient approaches are better than others. The rate of true detection is over 99.5%, while the failed alarm remains below 0.5%.

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Published

2014-08-25

Issue

Section

Computer Science