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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM4525

Machine Learning based Evidence Analysis in Digital Forensic Investigation

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM4525

Volume:

4 |

6 |

Jun 2020

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

RK

Reshma Khan

PR

Prof R.V.Mante

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Abstract

The integration of digital forensic investigation techniques in a Mobile Data Analyzer enhances its capabilities, allowing for detailed examination and extraction of evidentiary information from Mobile Data. This project focuses on developing a tool that aids forensic experts and investigators in parsing, analyzing, and presenting Mobile data to uncover valuable information that can support investigative findings in a legal or cybersecurity context. Additionally, visualizations and detailed logs enhance the presentation of findings, making it easier to track communication timelines, reconstruct events, and identify key participants in the chat. The integration of digital forensic investigation techniques in a Mobile Data Analyzer enhances its capabilities, allowing for detailed examination and extraction of evidentiary information from Mobile Data. This project focuses on developing a tool that aids forensic experts and investigators in parsing, analyzing, and presenting Mobile data to uncover valuable information that can support investigative findings in a legal or cybersecurity context. Additionally, visualizations and detailed logs enhance the presentation of findings, making it easier to track communication timelines, reconstruct events, and identify key participants in the chat.

KEYWORDS

Mobile Forensics Data Extraction Digital Evidence App Data Analysis Encryption Bypass Message Forensics.

Cite This Article

Reshma Khan, Prof R.V.Mante, "Machine Learning based Evidence Analysis in Digital Forensic Investigation," International Journal of Scientific Research in Engineering and Management, vol. 4, no. 6, Jun 2020.

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Publication Date

11/23/2024

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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