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Abstract
Smartphone has been widely popular in communications, social networking, online
shopping, online payment and so on in our daily life because of its abundant function and
powerful computing, storage, networking ability. On the other hand, criminal behavior that use
smartphone for swindle and theft of personal privacy has become increasingly severe. To
combat smartphone crime and protect the security of user information and property, diverse
data in smartphone can be important clue and evidence of criminal investigation, therefore the
data smart phone forensics has become an important issue need to be resolved. To solve the
issue, in this article several key technologies of Android smartphone forensics has been deeply
researched. The main work completed and the main achievements are as follows:
1. The Extended Model of Android Smartphone Forensics
An extended model of smartphone based on Android platform is designed aiming at the
security requirements in the process of Android smartphone forensics and combining the
characteristics of the traditional digital forensics model. The model contains complete forensic
process; secondly, in aspect of evidence analysis, smartphone geographic data, social data and
malicious processes are analyzed, which makes comprehensive analysis of the data in
smartphone and provides guidance for research of the key forensics technologies.
2. The Location Information Forensics Technology Based on File Carving.
Firstly, a new file carving algorithm is proposed after analyzing the produce of Location
information. The algorithm reassemble the database files (.db) and pictures files (.jpg) stored in
the smartphone according to head and tail characteristic of the known file types. In order to
make the geographic data more visualized, the visualization technology is used to mark the
user's action track on the map. Finally, experimental results show that the file carving algorithm
is robust, universal applicability and has good carving efficiency.
3. The WeChat Classification Technology Based on the Improved KNN Algorithm
In order to be able to quickly find the clues relevant to the case in a large number of
WeChat chats, an iterative improved KNN algorithm is presented for the WeChat chats
classification. The WeChat chats is processed through preprocessing, semantic similarity
calculation. The Comparison of classification results shows that the improved KNN algorithm
has higher accuracy and efficiency, realizing the accurate classification of social contact
information.
4. The Malicious Processes Detection Method Based on Physical Memory
Aiming at more and more malicious applications in Android platform, a malicious
万方数据
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