Main Article Content

Abstract

Now A days, criminal’s uses recent new technologies as well as technical methods to commit crimes
like money fraud, unethical hacking, fraud in various domains and prohibited access etc. So, the
investigation of such cases is tricky and more important task. That’s why need to do the forensic analysis. In
recent times digital forensics analysis has become a most important activity in crime investigation since
computers are gradually more used as tools to commit various crimes. Throughout forensic investigation the
digital devices such as desktops, , smart phones, notebooks, PDAs etc. found at the crime scene are collected
for further investigation .In digital forensic analysis, huge amount of files are generally need to examined.
Much of the data in those files consists of indistinct text, whose investigation by computer examiners is very
tough to accomplish. Digital forensics deals with such huge set of documents to collect the evidence from
computer devices. So, to do digital forensic analysis time limit play key role. So it’s a not easy task for
examiner to do such analysis in short period of time. Thus to do the digital forensic analysis of documents
within short period of time requires particular techniques to make such complex task in a simpler approach.
Such special technique includes document clustering. So, clustering algorithms are best choice for such
operations. This document clustering analysis is very helpful for crime investigation to analyze the
information from seized digital devices. In this paper we proposed novel approach to attain more efficient
document clustering in forensic analysis. The accuracy of clustering of documents may improve by means of
this novel approach.

Keywords

: Document Clustering, Forensic Analysis, Investigation, Crime

Article Details

How to Cite
[1]
Ms. Rajnee Kanoje and 2Dr. S. D. Choudhari, “A NOVEL APPROACH FOR DOCUMENT CLUSTERING IN DIGITAL FORENSIC ANALYSIS”, IEJRD - International Multidisciplinary Journal, vol. 3, no. 2, p. 7, Mar. 2018.