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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM21584

Email Spam Detection Using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM21584

Volume:

7 |

5 |

May 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PAD

Prof. Abhimanyu Dutonde

P.R

Prashik .P. Ramteke

AB

Akanksha Burade

RB

Rajani Bansod

PT

Pratham Telang

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Abstract

Nowadays, Email spam has become a big problem, with the fast growth of internet users, email spams are also increasing. People are using them for phishing, illegal and unethical practices and frauds. Sending malicious links through spam emails that can harm for our system and may also get into your system. It is very simple for spammers to create a fake profile and email account, they show like a real person in their spam emails, these spammers simply target people who are not aware of these frauds. then there is a need to identify those spam mails which are frauds, this project will identifies those spams using techniques of machine learning, this paper will discuss machine learning algorithm’s and apply all these algorithm’s to our dataset. it select the best algorithm, for this project algorithm will be chosen based on the best accuracy and precision in email spam detecting.

KEYWORDS

Email Spam Detection Machine Learning Neural Networks Support Vector Classifier Logistic Regression etc.

Cite This Article

Prof. Abhimanyu Dutonde, Prashik .P. Ramteke, Akanksha Burade, Rajani Bansod, Pratham Telang, "Email Spam Detection Using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 5, May 2023.

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Publication Date

5/22/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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Article Views

1

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3

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5

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Conflict of Interest

The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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