Application of Complex Network Analysis Theories for Crime Prevention in Nigeria

Criminals like every other individual in a society live and communicate within the network. Malicious entities make use of mobile phones to coordinate their nefarious activities, thereby generating telecommunication data that can be analyzed to gain valuable intelligence regarding how their crime communities are organized. These networks are in complex form of collective interactions and personal associations that constitutes a set of criminal individuals called the nodes, while the connections/communication links between the entities is referred to as edges. This paper focused on the theoretical application of complex network features in implementing BigData Active Security Framework (BASF) which could be used to generate the needed intelligence by security agencies for crime prevention in Nigeria. Mathematical characterizations for domain based Graph Partitioning (GP) problem are presented. The BASF merits, open challenges and remediation are articulated.