gang-cluster-analysis

Gang cluster analysis in a phone network identifies suspicious groups by analyzing shared devices and common contacts among phone numbers. It detects clusters of individuals connected through overlapping device usage and mutual contacts.

Shared device analysis for fraud detection identifies when multiple phone numbers or individuals use the same physical devices. It flags these overlapping device patterns to detect coordinated suspicious activity within a network.

To run cluster analysis, execute the skill with a file containing target phone numbers, such as passing a text file path to the command line interface. The tool processes the identifiers to detect interconnected groups.

Yes, you need access to phone network data and relevant Python libraries for graph analysis and data processing to detect common contacts. These libraries enable the network relationship mapping required for cluster identification.

Yes, phone network cluster analysis applies to threat intelligence scenarios by identifying potential gangs and suspicious groups. It maps shared relationships and common contacts to reveal coordinated threat networks.

Gang analysis for social network analysis is not suitable when you lack direct access to phone network data or sufficient shared device and common contact records. The cluster detection relies on these specific relationship inputs.