CISRI: A Crime Investigation System Using the Relative Importance of Information Spreaders in Networks Depicting Criminals Communications

Abstract

In this paper we propose a forensic analysis system called CISRI that helps forensic investigators determine the most influential members of a criminal group, who are related to known members of the group, for the purposes of investigation. In the CISRI framework, we describe the structural relationships between the members of a criminal group in terms of a graph. In such a graph, a node represents a member of a criminal group, an edge connecting two nodes represents the relationship between two members of the group, and the weight of an edge represents the degree of the relationship between those two members. Using this representation, we propose a method that determines the relative importance of nodes in a graph with respect to a given set of query nodes. Most current approaches that study relative importance determine the relative importance of a node under consideration by estimating the contribution of each query node individually to the importance of this node while overlooking the contribution of the query nodes collectively to the importance of the node under consideration. This may lead to results with low precision. CISRI overcomes this limitation by: (1) computing the contribution of the overall set of query nodes to the importance of a node under consideration, and (2) adopting a tight constraint calculation that considers how much each query node contributes to the relative importance of a node under consideration. This leads to accurate identification of nodes in the graph that are important, in relation to the query nodes. In the framework of CISRI, a graph is constructed from mobile communication records (e.g., phone calls and messages), where a node represents a caller and the weight of an edge reflects the number of contacts between two callers. We evaluated the quality of CISRI by comparing it experimentally with three comparable methods. Our results showed marked improvement.

Aim

The aim is to generate a forensic analysis system called CISRI to help forensic investigators determine the most influential members of a criminal group, who are related to known members of the group, for the purposes of investigation.

Scope

The scope of the CISRI is, to construct a graph from mobile communication records (e.g., phone calls and messages), where a node represents a caller and the weight of an edge reflects the number of contacts between two callers

Existing System

Digital Forensics has always been an evolving field of research. This is primarily due to the constantly changing devices and technologies that the investigator is interacting with. To keep pace with this change, forensic practitioners have spent a great deal of effort in seeking out and reviewing new techniques and systems. Computing devices, such as Smartphones, Tablets, and traditional PCs store a plethora of data as part of their normal functionality. The information gathered from these devices can assist in analyzing and reconstructing events that involved their owners. This permits the investigators to understand the case under investigation and to deduce relevant conclusions of evidential value. However, due to the amount of data that needs to be analyzed, investigators are facing one of the most serious concerns in Digital Forensics; namely the time and effort that need to be devoted to analyzing that data. It complicates the process of identifying relevant evidence as investigators are usually overwhelmed with a large amount of irrelevant data.

 Disadvantages

·      Existing system permits the investigators to understand the case under investigation and to deduce relevant conclusions of evidential value.

·      However, due to the amount of data that needs to be analyzed, investigators are facing one of the most serious concerns in Digital Forensics; namely the time and effort that need to be devoted to analyzing that data.

·      It complicates the process of identifying relevant evidence as investigators are usually overwhelmed with a large amount of irrelevant data.

Proposed System

CISRI overcomes limitations by: (1) computing the contribution of the overall set of query nodes to the importance of a node under consideration, and (2) adopting a tight constraint calculation that considers how much each query node contributes to the relative importance of a node under consideration.

• A system that analyzes criminal networks and determines the relative importance of their members with respect to other known members.

 • A tight constraint calculation of relative importance that ensures accurate identification of important members in a criminal network.

Advantages

·      CISRI can help forensic investigators determine the most influential members of a criminal group, who are related to known members of the group.

·      CISRI overcomes the limitations of current relative importance algorithms by adopting a tight constraint calculation.

·      To ensure accurate computation of relative importance, CISRI adopts mechanisms that address the problems of incomplete contribution and inconsistent contribution of query nodes.

·      CISRI outperformed the other algorithms.

·      CISRI leads to accurate identification of nodes in the graph that are important, in relation to the query nodes.

System Specification

Hardware Requirements

• Speed                  -    1.1 Ghz
• Processor              -    Pentium IV
• RAM                    -    512 MB (min)
• Hard Disk            -    40 GB
• Key Board                    -    Standard Windows Keyboard
• Mouse                  -    Two or Three Button Mouse
• Monitor                -     LCD/LED

 Software requirements

• Operating System              : Windows 7             
•  Front End                           : ASP.Net and C#
• Database                             : MSSQL
• Tool                                    : Microsoft Visual studio

References

Taha, K. ; Martin, T.A.; Alzaabi, M.," CISRI: A CRIME INVESTIGATION SYSTEM USING THE RELATIVE IMPORTANCE OF INFORMATION SPREADERS IN NETWORKS DEPICTING CRIMINALS COMMUNICATIONS", IEEE Transactions on Information Forensics and Security Volume: PP ,  Issue: 99 , June 2015.