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Published in:

Volume 7 Issue 11
November-2020
eISSN: 2349-5162

Unique Identifier

JETIR2011186

Page Number

394-400

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Title

A Survey of Authorship Identification in Digital Forensics based on Machine Learning Algorithms

ISSN

2349-5162

Cite This Article

"A Survey of Authorship Identification in Digital Forensics based on Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 11, page no.394-400, November-2020, Available :http://www.jetir.org/papers/JETIR2011186.pdf

Abstract

Authorship Identification is subfield of authorship analysis deals with finding the plausible author of anonymous messages. The Authorship identification problem of online messages is challenging task because cyber predators make use of obscurity of Cyberspace and conceal the identity. Cybercriminals make misuse of online communication for sending blackmail or a spam email and then attempt to hide their true identities to void detection. Authorship Identification of online messages is the contemporary research issue for identity tracing in cyber forensics. This is highly interdisciplinary area as it takes advantage of machine learning, information retrieval, and natural language processing. By performing the forensic analysis of online messages, empirical evidence can be collected. These evidences can be used to prosecute the cybercriminal in a court and punish the guilty. This way cybercrimes can be minimized up to certain extent by detecting the true identities. Therefore it is required to build up innovative tools & techniques to appropriately analyze large volumes of suspicious online messages. This paper compares the Performance of various classifiers in terms of accuracy for authorship identification task of online messages. Support Vector Machines, KNN, and Naïve Bayes classifiers are used for performing experimentation .This paper also investigate the appropriate classifier for solving authorship of anonymous online messages in the context of cyber forensics

Key Words

:Authorship Identification, Cybercrime, Cyber Forensics, Support Vector Machine, K-NN, Naïve Bayes

Cite This Article

"A Survey of Authorship Identification in Digital Forensics based on Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 11, page no. pp394-400, November-2020, Available at : http://www.jetir.org/papers/JETIR2011186.pdf

Publication Details

Published Paper ID: JETIR2011186
Registration ID: 303575
Published In: Volume 7 | Issue 11 | Year November-2020
DOI (Digital Object Identifier):
Page No: 394-400
ISSN Number: 2349-5162

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Cite This Article

"A Survey of Authorship Identification in Digital Forensics based on Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 11, page no. pp394-400, November-2020, Available at : http://www.jetir.org/papers/JETIR2011186.pdf




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