COI code: ICKIS01_014
Paper Language: English
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Authors A Distributed Approach for Spam Collection and Detection Using HoneypotsMoein Sarvi - Electricity and Computer Faculty Tarbiat Modares University Tehran, Iran
Ali Yazdiane Varjani - Electricity and Computer Faculty Tarbiat Modares University Tehran, Iran
Mohammad Ali Nazeri - Electricity and Computer Faculty Khorasgan (Isfahan) Branch Islamic Azad University
Abstract:Junk mail or spam is one of the serious problems of users in their daily electronic communications. Low working efficiency, disk space occupation, and phishing attacks are justsome spam consequences. With the advent of spam, the researchers have attemted at introduce methods to deal with thisphenomenon. Text-based Spam filtering can be considered as a text categorization problem. The most majority works in thisarea are dedicated to machine learning-based techniques. Despite the excellent results, machine learning algorithms are time consuming and highly dependent on the training data. In thispaper a method has been proposed for distributed spam detection base on honeypot traps and header features. Thisapproach obtains fresh training data through hybrid honeypot which deceives spammers in fidelity manner without any footprint. The accuracy of spam detection is high while using only header features along distributed classifier based on Naive Bayes algorithm. The results show increasing the number of classifier lead to improve accuracy measures like Recall and Precision.
Keywords:Spam, Honeypot, machine learning, Naïve Bayes, Honeyd
COI code: ICKIS01_014
how to cite to this paper:If you want to refer to this article in your research, you can easily use the following in the resources and references section:
Sarvi, Moein; Ali Yazdiane Varjani & Mohammad Ali Nazeri, 2014, A Distributed Approach for Spam Collection and Detection Using Honeypots, 1st International Conference on Knowledge Engineering, Information and Software, مشهد, دانشگاه آزاد اسلامي واحد مشهد, https://www.civilica.com/Paper-ICKIS01-ICKIS01_014.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Sarvi, Moein; Ali Yazdiane Varjani & Mohammad Ali Nazeri, 2014)
Second and more: (Sarvi; Yazdiane Varjani & Nazeri, 2014)
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The University/Research Center Information:
Type: state university
Paper No.: 25939
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