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Analysis of WeChat in Mobile and Computer Systems: Forensics Perspective

Authors: Zhou, Jiaxuan;

Analysis of WeChat in Mobile and Computer Systems: Forensics Perspective

Abstract

WeChat is one of the most popular applications in the world. By 2021, there were 1.24 billion users of WeChat. Many people call it the `super app` because it is an application for everything. Besides the basic messaging feature, it also supports online payment, video posts, news feeds, and more. Due to its wide usage, many criminals are using the platforms for illegal activities such as bank fraud, cyberbullying, and stalking. For these reasons, we need to understand WeChat forensically to assist investigators in cases involving WeChat. Previous research was mostly focused on the messaging of the WeChat application. However, artifacts of other features remain on the device undiscovered. These features can provide crucial evidence to a case such as geo-locations or monetary transactions. WeChat keeps updates monthly, and these updates may add new features or modify the data structure. The official website does not provide a detailed description of its features so it is hard for a non-WeChat user to understand the functionalities. Therefore, research is required to analyze the background, structure, and possible artifacts remaining of the WeChat app to assist practitioners who encounter WeChat in an investigation. This study included all platforms that WeChat provides, Windows, MacOS, Android, and iOS.

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Keywords

Digital forensics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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