The week's pick
Reseach Article
Analysis of File Component Requirements Using Digital Forensic XML on Social Media TikTok Applications
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 185 - Number 49 |
| Year of Publication: 2023 |
| Authors: Muhammad Romi Nasution, Mirajul Rifqi, Urfi Utami, Wirda Jannatul Jannah |
10.5120/ijca2023923327
|
Muhammad Romi Nasution, Mirajul Rifqi, Urfi Utami, Wirda Jannatul Jannah . Analysis of File Component Requirements Using Digital Forensic XML on Social Media TikTok Applications. International Journal of Computer Applications. 185, 49 ( Dec 2023), 45-52. DOI=10.5120/ijca2023923327
Abstract
Every smartphone application definitely leaves traces, especially XML file artifacts, for example the TikTok application has XML artifacts from records of activities carried out in the application. Starting from the beginning of the application being installed, the version of the application used, the time the application was accessed, videos or photos uploaded, newly registered or previously existing accounts and so on. This research found more than 150 XML files in the TikTok application using 3 accounts. However, not all of them are user activities, in general the activities carried out by users are recorded in the aweme_user file, even though the account has been deleted, it still leaves traces in the file. These activities are entering the application and recording video uploads. The file classification required for analysis in the context of this research is divided into 3 parts. These include very needed, less needed and not needed. Analysis is carried out especially on really needed parts such as the aweme_user file, version, search and others. Those that are less needed will still be analyzed to support the XML data contents of the very needed category files. After carrying out the analysis, it can be determined which files are isolated for further study. The data content of these files will be seen to see whether they contain important information about the perpetrator's activities. In this research, dozens of XML files can be identified.
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