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A Methodology for Cyber Crime Identification using Email Corpus based on Gaussian Mixture Model

by V.sreenivasulu, R. Satya Prasad
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 13
Year of Publication: 2015
Authors: V.sreenivasulu, R. Satya Prasad
10.5120/20616-3315

V.sreenivasulu, R. Satya Prasad . A Methodology for Cyber Crime Identification using Email Corpus based on Gaussian Mixture Model. International Journal of Computer Applications. 117, 13 ( May 2015), 29-32. DOI=10.5120/20616-3315

@article{ 10.5120/20616-3315,
author = { V.sreenivasulu, R. Satya Prasad },
title = { A Methodology for Cyber Crime Identification using Email Corpus based on Gaussian Mixture Model },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 13 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 29-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume117/number13/20616-3315/ },
doi = { 10.5120/20616-3315 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:59:19.573900+05:30
%A V.sreenivasulu
%A R. Satya Prasad
%T A Methodology for Cyber Crime Identification using Email Corpus based on Gaussian Mixture Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 13
%P 29-32
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The area of crime investigation has extended its roots to cyber media and has emerged exponentially with the technological strides. Among the various media used in Digital Forensics, Email Forensics took up the leading segment. In order to investigate the cyber crimes, there is an immense need to analyze the bulky email gatherings forensically. Data mining methods help in analyzing these large collections of data. Mixtures of data mining models along with the related methodologies are proposed in this paper to facilitate the email forensic assessor. The Performance is evaluated using False Rejection Ratio (FRR) and False Acceptance Ratio (FAR).

References
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  11. Aid4Mail Forensic, http://www. aid4mail. com/
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Index Terms

Computer Science
Information Sciences

Keywords

Email Forensics Data Mining Digital Forensics Word Net Query Analysis.

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