Privacy-preserving social network analysis for criminal investigations

Abstract

Social network analysis (SNA) is now a commonly used tool in criminal investigations, but evidence gathering and analysis is often restricted by data privacy laws. We consider the case where multiple investigators want to collaborate, but do not yet have sufficient evidence that justifies a plaintext data exchange. This paper proposes a solution for privacy-preserving social network analysis where several investigators can collaborate without actually exchanging sensitive private information. An investigator can request data from other sites to augment his view without revealing personally identifiable data. The investigator can compute important metrics by means of a SNA on the subject while keeping the entire social network unknown him.