Academic department under which the project should be listed

CCSE - Computer Science

Faculty Sponsor Name

Hossain Shahriar

No, as it did not require human subject or data gathering from participants.

Abstract (300 words maximum)

Classification is an important technique to deal with cybersecurity threats. In this paper, we detect spam emails from publicly available dataset using Naive Bayes and Neural Network (NN). The results from experiments show that for data sets with more balanced for classification, the accuracy of Naive Bayes is better than NN

Project Type

Poster

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Spam Email Detection: Comparison Between Naïve Bayes and Neural Network

Classification is an important technique to deal with cybersecurity threats. In this paper, we detect spam emails from publicly available dataset using Naive Bayes and Neural Network (NN). The results from experiments show that for data sets with more balanced for classification, the accuracy of Naive Bayes is better than NN