Email Spam Filtering Technique from Various Perspectives Using Machine Learning Algorithms

2021 ◽  
pp. 423-432
Author(s):  
Tushar Mehrotra ◽  
Gaurav Kumar Rajput ◽  
Manju Verma ◽  
Bhawana Lakhani ◽  
Niharika Singh
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Spam Filtering ◽  
Filtering Technique ◽  
Email Spam

scholarly journals A Machine Learning Based Email Spam Classification Framework Model: Related Challenges and Issues

2020 ◽  
Vol 9 (4) ◽  
pp. 3137-3144
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Spam Filtering ◽  
Important Work ◽  
Classification Framework ◽  
Framework Model ◽  
Spam Filters ◽  
Distinguishing Features ◽  
Email Spam

Spam emails, also known as non-self, are unsolicited commercial emails or fraudulent emails sent to a particular individual or company, or to a group of individuals. Machine learning algorithms in the area of spam filtering is commonly used. There has been a lot of effort to render spam filtering more efficient in classifying e-mails as either ham (valid messages) or spam (unwanted messages) through the ML classifiers. We may recognize the distinguishing features of the material of documents. Much important work has been carried out in the area of spam filtering which cannot be adapted to various conditions and problems which are limited to certain domains. Our analysis contrasts the positives methods as well as some shortcomings of current ML methods and open spam filters study challenges. We suggest some of the new ongoing approaches towards deep leaning as potential tactics that can tackle the challenge of spam emails efficiently.

scholarly journals Secured Mail Transformation System Using Machine Learnin

2021 ◽  
Vol 9 (VII) ◽  
pp. 1880-1886
Author(s):  
Rahul Anandpara
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Transformation System ◽  
Internet Users ◽  
Email Spam

Today, Email Spam has become a major problem, with Rapid increament of internet users, Email spams is also increasing. People are using email spam for illegal and unethical conducts, phishing and fraud. Sending malicious link through spam emails which can damage the system and can also seek in into your system. Spammer creates a fake profile and email account which is easier for them. These spammers target those peoples who are not aware about frauds. So there is a need to identify the fraud in terms of spam emails. In this paper we will identify the spam by using machine learning algorithms.

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