International Journal of Computer
& Organization Trends

Research Article | Open Access | Download PDF

Volume 4 | Issue 2 | Year 2014 | Article Id. IJCOT-V7P304 | DOI : https://doi.org/10.14445/22492593/IJCOT-V7P304

Bayesian Decision Framework for an Efficient Spam Filtering in Social Network

T.Priyanka

Citation :

T.Priyanka, "Bayesian Decision Framework for an Efficient Spam Filtering in Social Network," International Journal of Computer & Organization Trends (IJCOT), vol. 4, no. 2, pp. 60-64, 2014. Crossref, https://doi.org/10.14445/22492593/IJCOT-V7P304

Abstract

Internet email is one of the most popular communication methods in business and personal lives. However, spam is causing a major problem in email systems. The wide growth of unwanted emails has prompted the growth of numerous spam filter techniques. Many Filtering techniques had been used for identifying spam emails, treats spam filtering as a binary classification problem. i.e. the in-coming email is either spam or non-spam. Current work proposes three-way decision approach to Social network Aided Personalized and effective spam filter (SOAP) based on Bayesian decision theory. Three-way decision approach based on Bayesian decision theory is introduced to SOAP for classification of spam details. In each node, components such as social interest-based spam filtering, adaptive trust management and social closeness-based spam filtering is integrated in the Bayesian filter to classify the spam and non spam details. The key advantage of the proposed is that the unresolved cases must be re-examined by collecting additional information from the components of the node. Experimental results shows that the current approach minimizes the error rate of classifying a legitimate email to spam, and offers better spam weighted and precision accuracy.

Keywords

Social network , SOAP, Bayesian theory, three-way decision, Spam filter

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