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Mitigating Spam Emails Menace Using Hybrid Spam Filtering Approach

Abstract

Spam is a known problem to email users. Sending spam emails is one of the easiest form of advertising and hence a useful medium of communication like email is abused by spammer to send junk email. Most antispam solution focus only on analysing text of the body of email messages for detecting spam emails. We have developed a spam filter that separates spam from non-spam (ham) emails by analysing header, URL, body, and attachments. Header and URL are checked against rules and text of body and attachments are checked by Bayesian classifier and Apriori algorithm. Only (*.rtf, *.txt, *.docx, *.doc,*.pdf) attachment files are examined. The experimental results reveal that checking attachments of emails played significant role in spam detection and hence attachment checks should be extended to more file types for better spam detection.

Keywords

  • Email
  • Spam
  • Bayesian
  • Apriori

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Correspondence to Stanlee Nagaroor .

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Nagaroor, S., Patil, G.A. (2018). Mitigating Spam Emails Menace Using Hybrid Spam Filtering Approach. In: Shetty, N., Patnaik, L., Prasad, N., Nalini, N. (eds) Emerging Research in Computing, Information, Communication and Applications. ERCICA 2016. Springer, Singapore. https://doi.org/10.1007/978-981-10-4741-1_20

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  • DOI: https://doi.org/10.1007/978-981-10-4741-1_20

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