An Efficient Spam Classification Filter as a Naive Bayes Classifier Web Application

Owing to the widespread expansion of internet users, email has emerged as a vital means of exchanging information worldwide, both personally and professionally, as it is a suitable and affordable means of doing so. It is probably mistreated or abused, though. One instance of this is the spam email, also known as non-legitimate email, which is distributed randomly to a large number of recipients and contains irrelevant content. Thus, Computer security has long been concerned about spam emails. They pose a serious risk to the computer network and computer users alike. The necessity for automatic email management systems, such as email filters that can distinguish between valid and spam emails, phishing email classifiers, and folder grouping, has expanded along with the exponential growth in the usage of email in business communication. We devised a resolution for this problem: an online application that uses the Naive Bayes classification method to separate incoming messages into spam and ham categories.

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Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/acroset62108.2024.10743587
Citations
4
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
1.40
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article

An Efficient Spam Classification Filter as a Naive Bayes Classifier Web Application

Ratnesh Kumar Dubey, Shashikant Gupta, Nidhi Dandotiya, Aravendra Kumar Sharma et al.
4 citations
Network Security and Intrusion Detection
1.40
article

An Efficient Spam Classification Filter as a Naive Bayes Classifier Web Application

Ratnesh Kumar Dubey, Shashikant Gupta, Nidhi Dandotiya, Aravendra Kumar Sharma, Suraj Sharma
article en
4 citations

Abstract

Owing to the widespread expansion of internet users, email has emerged as a vital means of exchanging information worldwide, both personally and professionally, as it is a suitable and affordable means of doing so. It is probably mistreated or abused, though. One instance of this is the spam email, also known as non-legitimate email, which is distributed randomly to a large number of recipients and contains irrelevant content. Thus, Computer security has long been concerned about spam emails. They pose a serious risk to the computer network and computer users alike. The necessity for automatic email management systems, such as email filters that can distinguish between valid and spam emails, phishing email classifiers, and folder grouping, has expanded along with the exponential growth in the usage of email in business communication. We devised a resolution for this problem: an online application that uses the Naive Bayes classification method to separate incoming messages into spam and ham categories.

ITM University (IN)
Openalex Percentile: Top 17%
Network Security and Intrusion Detection
1.40
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An Efficient Spam Classification Filter as a Naive Bayes Classifier Web Application — Ratnesh Kumar Dubey, Shashikant Gupta, et al. · (2024) | TGRS Research Map | TGRS