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Survey: Author Identification using Data Mining Techniques

Author(s):

Aishwarya Chavan , Modern Education Society's College of Engineering; Yashodhara Jamdade, Modern Education Society's College of Engineering; Priyanka Hundalekar, Modern Education Society's College of Engineering; Poonam Kamble, Modern Education Society's College of Engineering

Keywords:

Cybercrime; Author Identification; Naïve Bayes Classifier; SVM

Abstract

With the rapid growth of the Internet and the expansion of its users, the Internet is becoming an ideal platform for the criminal activities which mainly includes committing fraud, stealing identities, or violating privacy, and etc. The sender can hide their true identity by creating sender’s address; Route through an anonymous server and by using multiple usernames via different anonymous channel and perform the crime. This type of the message spread the incorrect information and evidence in society that give rise to social conflict. This paper presents a survey of the literature on author identification schemes and different techniques up till date. The paper outlines an overview of the author identification schemes. The different algorithms adopted for the schemes are discussed. Outlining the application and merits of the same.

Other Details

Paper ID: IJSRDV6I100116
Published in: Volume : 6, Issue : 10
Publication Date: 01/01/2019
Page(s): 99-101

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