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Forensic Browser of Twitter based on Web Services

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 29
Year of Publication: 2020
Authors:
Revani Saputra, Imam Riadi
10.5120/ijca2020920832

Revani Saputra and Imam Riadi. Forensic Browser of Twitter based on Web Services. International Journal of Computer Applications 175(29):34-39, November 2020. BibTeX

@article{10.5120/ijca2020920832,
	author = {Revani Saputra and Imam Riadi},
	title = {Forensic Browser of Twitter based on Web Services},
	journal = {International Journal of Computer Applications},
	issue_date = {November 2020},
	volume = {175},
	number = {29},
	month = {Nov},
	year = {2020},
	issn = {0975-8887},
	pages = {34-39},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume175/number29/31636-2020920832},
	doi = {10.5120/ijca2020920832},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Twitter is a social media that can be accessed through smartphones and desktops. The large number of users makes Twitter inseparable from crimes including pornography, online gambling and hate speech. In this study, the steps used are collection, examination and analysis. This study uses a laptop as an object that is scenario in a state of opening Twitter via the Google Chrome browser with two modes, namely public mode and private mode. The research used the help of forensic tools, namely ftk imager, dumpIT, belkasoft ram capturer, XhD, browser history viewer, browser history capturer, and cached video viewer. This research produces digital evidence with google chrome browser in public mode and google chrome browser in private mode. In the condition of using the browser in public mode with indicators in the form of text posts, link posts, images, and videos, the research succeeded in getting all the evidence that was sought. Meanwhile, in the private mode google chrome browser managed to get evidence with a success of 50%, namely in the form of text posts and link posts. While the remaining 50% is not found for private mode browsers, namely in image posts and video posts.

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Keywords

Forensics, Web, Browsers, Pornography, Twitter