In the context of preventing and fighting crime, the analysis of mobile phone traffic, among actors of a criminal network, is helpful in order to reconstruct illegal activities on the basis of the relationships connecting those specific individuals. Thus, forensic analysts and investigators require new advanced tools and techniques which allow them to manage these data in a meaningful and efficient way. In this paper we present LogAnalysis, a tool we developed to provide visual data representation and filtering, statistical analysis features and the possibility of a temporal analysis of mobile phone activities. Its adoption may help in unveiling the structure of a criminal network and the roles and dynamics of communications among its components. Using LogAnalysis, forensic investigators could deeply understand hierarchies within criminal organizations, for e.g., discovering central members who provide connections among different sub-groups, etc. Moreover, by analyzing the temporal evolution of the contacts among individuals, or by focusing on specific time windows they could acquire additional insights on the data they are analyzing. Finally, we put into evidence how the adoption of LogAnalysis may be crucial to solve real cases, providing as example a number of case studies inspired by real forensic investigations led by one of the authors.
In this paper we present our tool LogAnalysis for forensic visual statistical analysis of mobile phone traffic. LogAnalysis graphically represents the relationships among mobile phone users with a node-link layout. Its aim is to explore the structure of a large graph, measure connectivity among users and give support to visual search and automatic identification of organizations. To do so, LogAnalysis integrates graphical representation of network elements with measures typical of Social Network Analysis (SNA) in order to help detectives or forensic analysts to systematically examine relationships. The analysis of data extracted from mobile phone traffic logs has a fundamental relevance in forensic investigations since it allows to unveil the structure of relationships among individuals suspected to be part of criminal organizations together with the role they play inside the organization itself. To this purpose, the Social Network Analysis (SNA) methods were heavily employed in order to understand the importance of relationships. Interpretation and visual exploration of graphs representing phone contacts over a given time interval may become demanding, due to the presence of numerous nodes and edges. Our main contribution is an interface that enables systematic analysis of social relationships using visual different techniques and statistical information. LogAnalysis allows a deeper and clearer understanding of criminal associations while evidencing key members inside the criminal ring, and or those working as link among different associations