AI at Borders: Detecting Deception in Real Time

AI-powered surveillance systems are redefining border control by detecting deception through micro-expressions, stress patterns, and speech anomalies.

In an era of increasing global mobility, ensuring the security of national borders has become a critical priority for governments worldwide. Airports and seaports serve as vital entry points, making them prime targets for illegal immigration, human trafficking, and other transnational crimes. Traditional security measures, such as document verification and background checks, are no longer sufficient to address the growing sophistication of deception techniques. As a result, behavioural deception detection technologies, including suspect detection systems, layered voice analysis, and AI-based emotion detection cameras, have emerged as key tools in identifying individuals attempting to enter countries under pretences.

Behavioural deception detection relies on analysing micro-expressions, physiological responses, and speech patterns to identify inconsistencies that may indicate dishonesty. One such technology is the Suspect Detection System (SDS), which combines biometric analysis, facial recognition, and stress-level assessment to evaluate passengers at border checkpoints. This system works by asking targeted questions and measuring involuntary physiological responses, such as eye movement, pulse rate, and skin conductivity. SDS has been successfully deployed in various countries to flag suspicious travellers before they proceed further into immigration clearance.

Another effective technology in deception detection is Layered Voice Analysis (LVA). Unlike traditional polygraph tests, which require physical sensors, LVA analyses vocal characteristics to detect emotional stress and cognitive dissonance. It evaluates variations in pitch, tone, and speech hesitation to identify potential deceptive behaviour. Used by security agencies worldwide, LVA has proven particularly effective in uncovering inconsistencies in the statements of travellers suspected of using forged documents or concealing their true intentions. Its ability to provide real-time deception assessments makes it a valuable tool in high-traffic areas such as airports and seaports.

AI-driven emotion-detection cameras further enhance border security by analysing facial expressions and body language. These cameras use deep learning algorithms to detect micro-expressions that are difficult to conceal, such as fleeting signs of anxiety or nervousness. By integrating these systems with existing security infrastructure, authorities can identify high-risk individuals with greater accuracy. Several countries, including the United States, the Netherlands, and Israel, have incorporated AI-based surveillance at major entry points to improve security screening processes.

Globally, deception detection measures have led to significant breakthroughs in security. In the Netherlands, the Schiphol Airport employs AI-driven travel surveillance to assess passenger risk based on behaviour patterns and travel history. In India, deception detection has played a crucial role in curbing illegal immigration at major international airports, such as Indira Gandhi International Airport in New Delhi. In 2024 alone, Delhi Police arrested 203 individuals involved in immigration fraud, marking a 107% increase from the previous year. These arrests were made possible through enhanced behavioural analysis techniques and advanced document verification methods.

Statistical insights further emphasise the importance of deception detection in immigration security. In 2024, Delhi Police's crackdown on fraudulent immigration agents led to a record number of arrests, with most offenders hailing from Punjab (70), Haryana (32), Delhi (25), Uttar Pradesh (25), and West Bengal (17). Such figures underscore the prevalence of immigration fraud across various regions and highlight the need for ongoing advancements in deception detection technologies.

The scope of behavioural deception detection in India is vast, with significant opportunities for enhancement. By integrating AI-powered emotion detection, real-time voice analysis, and biometric monitoring, Indian airports and ports can strengthen their security frameworks. Investing in advanced training programmes for immigration officers, fostering international collaborations, and leveraging AI-driven analytics can further bolster national security. Public awareness campaigns on the risks of immigration fraud can also act as a deterrent, ensuring a more secure and transparent border control system.

(Dr. Kumar is a retired IPS officer and forensic consultant to the Assam government. Reddy is Forensic Psychologist and Industrial & Corporate Security Professional.)