- The Ministry of Home Affairs is integrating Artificial Intelligence (AI) to strengthen internal security through predictive policing, cyber monitoring, and fraud detection.
Need for AI in Internal Security
- Reactive Policing: India’s traditional policing responds after crimes, causing delays. E.g., cybercrime surged from 10.29 lakh (2022) to 28.15 lakh (2025).
- Digital Threats: Online fraud like phishing and identity theft caused losses of ₹22,812 crore in 2024, showing the need for real-time AI detection.
- Data Complexity: Agencies handle massive data from finance, telecom, immigration, social media, and CCTV, requiring AI analytics for fast threat identification.
- Global Trends: AI tools in predictive policing and facial recognition have reduced crime by 17–40% globally, proving their preventive effectiveness.
Role of AI in Internal Security
- Predictive Policing: Uses historical crime, GIS, and temporal patterns to forecast high-risk zones. E.g., cities using AI have crime prediction accuracy of ~25–35%.
- Cyber Detection: Monitors dark web, scam sites, and phishing campaigns by identifying suspicious patterns in real time. E.g., global cyber threats rose 15% in 2024.
- Fraud Prevention: Detects mule accounts, unusual transactions, and money laundering using AI-driven real-time analysis. E.g., the RBI estimates ₹20,000 crore in annual losses without such systems.
- Child Safety: Screens Child Sexual Exploitative and Abuse Material (CSEAM) and harmful content. E.g., hash-based detection speeds takedown by up to 70%.
- Border Security: Supports intelligent traveller profiling, risk assessment, and identity verification. E.g., the IVFRT 3.0 (Immigration, Visa, Foreigners Registration and Tracking) system will enhance secure, real-time immigration management.
Government Initiatives
- I4C AI Helpline (1930): Multilingual AI-enabled complaint registration for faster cybercrime reporting.
- Mule Hunter App: Developed with RBI Innovation Hub, identifies mule accounts and fraud in banking systems.
- Proactive Monitoring Tool (CSEAM): Developed by CDAC to detect child abuse material online.
- Surakshini Initiative: Creates a hash bank of illegal content for automated detection and preventive moderation.
- IVFRT 3.0: AI/ML-based traveller profiling, exploring blockchain for secure immigration records.
- Forensic AI Tools: Used in digital and cybercrime investigations; document forgery detection is under development.
|
Challenges with AI in Internal Security
- Privacy Risk: AI surveillance may breach the fundamental right to privacy (Puttaswamy, 2017) via large-scale biometric data collection.
- Data Security: Cybercrime surged from 10.29 lakh (2022) to 28.15 lakh (2025), exposing personal and financial data.
- Technology Maturity: Certain AI applications, such as document forgery detection and automated behavioural analysis, remain in their nascent stages.
- Algorithmic Bias: AI trained on skewed data can lead to discriminatory outcomes in law enforcement.
- Regulation Gaps: DPDP Act, 2023, lacks AI-specific rules, creating gaps in accountability and oversight.
AI Roadmap for Internal Security
- AI Governance: Establish dedicated AI laws with ethical standards, accountability, and independent audits, building on the DPDP Act 2023 framework.
- Data Ecosystem: Integrate anonymised data from the Indian Cyber Crime Coordination Centre (I4C), banks, telecom, and social media for real-time threat detection, safeguarding personal and financial data.
- Ethical AI: Mandate Explainable AI to reduce algorithmic bias, enhance transparency, and allow judicial or supervisory review in predictive policing.
- Innovation Hubs: Set up AI labs and training centres in police and paramilitary units, fostering collaboration with IITs, startups, and academia.
- Citizen-Centric: Deploy AI in multilingual helplines (1930), Surakshini initiative, and predictive threat management for safer communities and improved grievance redressal.
AI is a force multiplier, enabling a shift from reactive policing to predictive, data-driven internal security.
Its success hinges on balancing innovation with privacy, ethics, and accountability for a resilient, citizen-centric system.
Reference: The Indian Express
PMF IAS Pathfinder for Mains – Question 616
Approach
- Introduction: Write a contextual introduction about the AI in internal security.
- Body: Write about the increasing use of Artificial Intelligence in India’s internal security, highlight the challenges and suggest an AI roadmap for internal security.
- Conclusion: Emphasis on a predictive, preventive, and proactive AI approach to redefining India’s internal security architecture.
