The Ministry of Railways’ information technology (IT) backbone — the Centre for Railway Information Systems (CRIS) — has undertaken two major initiatives to secure the digital infrastructure of Indian Railways and streamline its information and operations systems.
“The implementation of IRSOC will significantly enhance the cybersecurity monitoring capabilities of Indian Railways, leading to a substantial reduction in Mean Time to Detect and Mean Time to Respond through the deployment of advanced security solutions such as Security Information and Event Management (SIEM), Security Orchestration Automation and Response (SOAR), Endpoint Detection and Response (EDR), and Network Detection and Response (NDR),” the report stated.
Security Operations Centre for Indian Railways and an enterprise-wide analytics framework are included, stated CRIS, marking its 40th Foundation Day, in a report.
The report stated that the implementation of IRSOC will enhance the cybersecurity monitoring capabilities of Indian Railways. It will lead to a major reduction in Mean Time to Detect and Mean Time to Respond through the deployment of advanced security solutions.
The analytics framework will function by unifying data from various applications into a single Artificial Intelligence/Machine Learning (AI/ML)-enabled decision support system. CRIS aims to significantly improve operational efficiency, safety, asset management, and passenger services.
Some of the areas where Indian Railways is looking to implement this decision support system include the growth of freight and passenger revenue, increasing market share, and improving profitability. It will also be used to enhance passenger safety and monitor asset performance and inventory levels.
The data revolution within Indian Railways is also being seen as a model for other public infrastructure sectors. An official involved in CRIS's digital vision said, "What we are building is more than just a dashboard; it is a predictive governance model.
Railways are no longer steel tracks and locomotives; they are now a complex mesh of data, passengers, sensors and machines." Industrial Analysts have warned that the success of this initiative depends on data integrity, ethical AI employment. They stress the need for continuous training of staff and real-time policy adaptation.
