The government has taken action against approximately 1.4 lakh mobile numbers implicated in
as a measure to curb digital
, it was announced during a meeting chaired by financial services secretary Vivek Joshi on cybersecurity in the
“The department of telecommunications (DoT) analysed 35 lakh Principal Entities (PEs) sending bulk SMSs. Out of these, 19,776 Principal Entities involved in sending malicious SMSs are blacklisted and 30,700 SMS Headers and 1,95,766 SMS templates have been disconnected,” the government said in an official note.
Till date, more than 500 arrests have been made around 3.08 lakh SIMS blocked, around 50,000 IMEI blocked, and 592 fake links/ APK and 2,194 URLs blocked since April 2023.
Other points discussed during meeting
Among the topics addressed was the integration of banks and financial institutions into the Citizen Financial Cyber Fraud Reporting and Management System (CFCFRMS) platform through API integration.
Integration of CFCFRMS platform with the National Cybercrime Reporting Portal (NCRP) to centralise the platform that will enable effective collaboration between Police, Banks, and Financial Institutions, allowing for real-time monitoring and prevention of fraudulent activities was deliberated, the government said.
The banks and financial institutions are also required to phase out the use of regular 10-digit numbers and shift to using specific number series such as ‘140xxx’ for commercial or promotional activities as prescribed by TRAI.
The meeting also assessed the action points from the previous session held in November and reviewed the readiness of banks and other financial institutions in addressing challenges related to cyber security in the financial sector.
AI to detect mobile connections
During the meeting, it was noted that the DoT has developed ASTR, an AI-machine learning-based engine, to detect mobile connections taken on fake/forged documents. Banks and financial institutions were also told to conduct additional customer awareness and sensitisation programmes in regional languages on the security of digital payments.