The way you walk and your footsteps could be used as a biometric at airport security instead of fingerprinting and eye-scanning.

Researchers at The University of Manchester in collaboration with the University of Madrid have developed a state-of-the-art artificial intelligence (AI), biometric verification system that can measure a human’s individual gait or walking pattern. It can successfully verify an individual simply by them walking on a pressure pad in the floor and analysing the footstep 3D and time-based data.

The results, published in one of the top machine learning research journals, the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) earlier this year, showed that, on average, the AI system developed correctly identified an individual almost 100% of the time, with just a 0.7 error rate.

Physical biometrics, such as fingerprints, facial recognition and retinal scans, are currently more commonly used for security purposes. However, so-called behavioural biometrics, such as gait recognition, also capture unique signatures delivered by a person’s natural behavioural and movement patterns. The team tested their data by using a large number of so-called ‘impostors’ and a small number of users in three different real-world security scenarios. These were airport security checkpoints, the workplace, and the home environment.

Omar Costilla Reyes, from Manchester’s School of School of Electrical and Electronic Engineering and who led the research, explains: “Each human has approximately 24 different factors and movements when walking, resulting in every individual person having a unique, singular walking pattern. Therefore monitoring these movements can be used, like a fingerprint or retinal scan, to recognise and clearly identify or verify an individual.”


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