Data security and threat modeling for smart city infrastructure

Abstract

Smart city opens up data with a wealth of information that brings innovation and connects government, industry and citizens. Cyber insecurity, on the other hand has raised concerns among data privacy and threats to smart city systems. In this paper, we look into security issues in smart city infrastructure from both technical and business operation perspectives and propose an approach to analyze threats and to improve data security of smart city systems. The assessment process takes hundreds of features into account. Data collected during the assessment stage are then imported into an algorithm that calculates the threat factor. Mitigation strategies are provided to help reducing risks of smart city systems from being hacked into and to protect data from being misused, stolen or identifiable. Study shows that the threat factor can be reduced significantly by following this approach. Experiments show that this comprehensive approach can reduce the risks of cyber intrusions to smart city systems. It can also deal with privacy concerns in this big data arena.