WeChat Forensics Method of Android Smart Phone Based on Improved NBC

Abstract

At present, in the investigation stage, public security organs, procuratorial organs and people's courts often need to conduct electronic data forensics analysis on criminals' WeChat and other social software to obtain sensitive information. This paper proposes a forensic analysis method based on chat history data of Wechat on Android smart phone. By using an Improved Naive Bayes Algorithm with redefinable the weights of the feature words, an improved Naive Bayes Classifier (NBC) model is established. The classifier is used to classify the chatting texts in WeChat, in order to find the sensitive information in the chatting texts efficiently. Experiments show that this model can improve the efficiency of acquiring sensitive information in WeChat, and has obvious effects on saving evidence collection time and improving the efficiency of criminal detection.