Spam Detection Approaches and Strategies: A Phenomenons

Abstract

The massive increase of spam is posing a very dangerous and serious threat to our email and social networks. It is pertinent and imperative to step up the spam detection approach and strategies in email and social networks. In recent years online spam has become a major problem for the sustainability of the internet globally, Excessive amounts of spam are not only reducing the quality of information available on the email and social networks but also creating concern among the users of email and various social networks. This paper aims to analyze existing research works in spam detection strategies and approaches, state of art, the phenomenon of spam detection, to explore the rudiment of spam detection, to proposed detection scheme and potential online mitigation schemes. The paper will surveys various anti spam strategies for email and social networking. In the literature we have studied that many anti spam strategies have been discovered and work on but they are still open challenges to these different approaches and techniques, while some of them are highlighted in this articles. It is very important to work on spam detection and reposition it for the better of the world.. General Terms

Logistic Regression Based Classification of Spam and Non-Spam Emails

“…al. [1] observes the techniques for reducing the logistic loss function in the spam filtering problem and carries out performance analysis of different techniques. The goal of this paper is to identify if the email is spam or not and recognizes logistic regression as one of the best technique to categorize an email as spam or not spam.…”

“…al. [7] targets to investigate available research works in spam detection approaches, the process which is being followed in these methods, and other mitigation systems. Many antispam strategies are surveyed for email and social networking in this paper.…”

A Survey on Various Machine Learning and Deep Learning Algorithms used for Classification of Spam and Non-Spam Emails

“…al. paper [1] observes the techniques for reducing the logistic loss function in the spam filtering problem and carries out performance analysis of different techniques. The goal of this paper is to identify if the email is spam or not and recognizes logistic regression as one of the best technique to categorize an email as spam or not spam.…”

“…Results show that naïve Bayesian classifier has more accuracy than support vector machine since the error rate is very low in Naïve Bayes classifier. The paper [7] targets to investigate available research works in spam detection approaches, the process which is being followed in these methods, and other mitigation systems. Many anti-spam strategies are surveyed for email and social networking in this paper.…”