Research On Association Analysis Method Based On Mobile Digital Forensic Data

With the rapid development of mobile Internet technology,smart mobile terminals have become increasingly popular and become an indispensable tool in people's lives.While improving the convenience and richness of the masses of life,it also gives criminals the opportunity to use the mobile terminal to conduct illegal activities such as SMS fraud,electronic viruses,information theft,malware,etc.,which have seriously affected people's long-term stability in daily life and society.In order to combat such crimes and regulate social governance,mobile forensics technology came into being.At present,China's mobile forensics technology still stays in the stage of collecting electronic data and longitudinal analysis,and it is difficult to cope with the complex situation of massive data in today's intelligent mobile terminals.How to find out valuable information from the cumbersome data,and then make up for the shortcomings of the current mobile forensics technology is an urgent problem to be solved.This paper firstly elaborates the research background and significance of mobile digital forensics and data association mining,and deeply analyzes the research status and development trend of digital forensics and association mining at home and abroad,and introduces the basic knowledge and implementation technology related to mobile forensic data association analysis.Including the concept of electronic evidence,K-means clustering algorithm,Apriori algorithm,FP-Growth algorithm,MySQL database,etc.This paper analyzes the mobile forensic data from the perspectives of relevance and association rules.Aiming at the social relationship problem of forensic target,this paper proposes a correlation analysis method based on user intimacy and correlation,and verified by experiment The feasibility of the method effectively mines the hidden user relationship in basic communication and social applications.For the analysis of association rules of mobile forensic data,this paper proposes an improved algorithm based on FP-Growth and applies the method to In the forensic analysis,the user's high and low frequency association rules are effectively extracted,and the daily behavior characteristics of the user are depicted from the side,which improves the accuracy of forensic analysis.The association analysis method based on mobile forensic data proposed in this paper can not only establish the relationship between user contacts,but also analyze the user's characteristics from multiple dimensions,and effectively impove the shortcomings of existing forensic techniques.To some extend,the results of this article can improve the accuracy of forensic identification and provides more effective information for the further research about the case.