A Cybersecurity Framework for Traffic Management in Indian Smart Cities

Abstract

As the concept of smart cities has gained momentum in India, the need for intelligent traffic management systems has risen, with the growing reliance on open traffic data for real-time monitoring, congestion management, and mobility planning. The challenges of cybersecurity are also significant with the integration of open data sources as data manipulation, unauthorized access, denial-of-service attacks, and privacy breaches occur. In this paper, the authors have tried to propose a cyber security framework for resilient traffic management in smart cities of India with the help of open traffic data. The proposed framework includes data validation, anomaly detection, access control systems, encryption methods and real time threat monitoring for improving the security and reliability of traffic management operations. The framework was tested against publicly available traffic data with more than 500,000 traffic records from urban transportation networks. Machine learning–based methods for anomaly detection were used in experimental implementation to detect malicious traffic data and possible cyberattacks. The results show that the proposed method succeeds in 96.4% of the attacks and only has 3.8% false positive rate, while the system also has increased resilience by 28% compared to traditional traffic monitoring methods. Additionally, secure data processing mechanisms minimised the risk of unauthorised data modification whilst the real time processing requirements were met. The results show that embedding cybersecurity capabilities into an open traffic data platform can greatly increase the reliability, security and operational efficiency of smart city traffic management systems. The suggested framework will give a concrete basis for building intelligent transportation infrastructures that are secure and resilient in emerging smart cities of India.