Emergence of AI in India’s Internal Security Architecture

Why in the News?

The Parliament's Standing Committee on Communications and Information Technology, published a report titled "Impact of Emergence of Artificial Intelligence and Related Issues,"

More on the news

• The report highlighted the implications of Artificial Intelligence (AI) for India's internal security.
• AI facilitates real-time surveillance, predictive policing, behavioural analysis, and crime pattern recognition, enabling faster and more informed decision-making.

Role of AI in India's Internal Security Architecture

• Modernizing Law Enforcement and Paramilitary Operations:
  • Police Forces and CCTNS 2.0: The National Crime Records Bureau (NCRB) is upgrading the Crime and Criminal Tracking Network & Systems (CCTNS) to use AI for predicting Acts and Sections from FIRs, multilingual queries, identifying crime hotspots, and resolving entities to build comprehensive criminal profiles.
  • Border Security and Paramilitary Forces: AI-powered drones, robotics, and computer vision systems are being deployed for border surveillance, intrusion detection, and terrain analysis, especially in hazardous or porous areas. E.g.-
    • CRPF: Utilizes AI for crowd forecasting, fake news monitoring, and multilingual Natural Language Processing (NLP) to decode insurgent communications.
    • CISF: Implements centralized AI surveillance, predictive threat alerts, and AI-powered baggage screening at airports.
    • NSG: Develops the National IED data management software (NIDMS) using AI for language processing, image analysis, and predictive threat awareness.
• Combating Cybercrime and Financial Fraud: The Indian Cyber Crime Coordination Centre (I4C) relies heavily on AI to modernize its reporting, investigation, and mitigation strategies.
  • National Cybercrime Reporting Portal (NCRP): An AI solution is being fine-tuned to automatically classify cybercrime complaints, helping law enforcement prioritize cases efficiently. 
    • I4C is also implementing an AI-assisted, multilingual complaint registration system for the 1930 cybercrime helpline.

• Mule Accounts and Financial Fraud: In collaboration with IIT Bombay and the Reserve Bank Innovation Hub (RBIH), I4C uses AI and machine learning algorithms (like "Mulehunter.ai") to assign suspect scores to financial transactions and bank accounts.
• Real-Time Fraud Detection: Comprehensive advisories require banks to use AI/ML tools for real-time transaction monitoring, behavioral prompts for risky transfers, and embedded checks using the Financial Fraud Risk Indicator database.
• Monitoring Digital Threats, the Dark Web, and Harmful Content: Security agencies are actively using AI to scan open-source intelligence and encrypted platforms.
  • Dark Web and Threat Analytics: The National Cybercrime Threat Analytics Unit (NCTAU), under I4C, utilizes AI-based tools to track dark web activities, including data breaches, illicit marketplaces, and cybercrime-as-a-service.
  • Child Sexual Exploitation and Abuse Material (CSEAM): A Proactive Monitoring Tool (PMT) developed by CDAC Mumbai screens cyber tiplines for CSEAM. 
    • Furthermore, the SURAKSHINI initiative is establishing a dedicated mitigation center and a hashbank to proactively detect and prevent the upload of non-consensual intimate imagery and CSEAM on social media.
• Deepfakes and Misinformation: The NCTAU identifies unlawful deepfakes and issues statutory takedown notices to Social Media Intermediaries (SMIs).

Conclusion 

AI cannot serve as an isolated, dependable source for administrative decisions. Governance requires a hybrid model, i.e. AI provides data-driven insights, while human administrators provide empathy and moral oversight. For robust implementation, India must enforce regular algorithmic audits, maintain a human-in-the-loop framework, and strictly implement the Digital Personal Data Protection Act.