Developing a Privacy-preserving Retinal Biometric Recognition System: Mahshid Sadeghpour
Channel: The Royal Society of Victoria
Date: 2022-11-29

Biometrics are physiological traits of individuals that are unique to them, e.g., fingerprints or the eye’s retina. Biometrics, although convenient for the purpose of human recognition, contain sensitive personal information about individuals, such as their ethnicity and health conditions. It is imperative to protect the private information in biometrics.

Because biometric data is “fuzzy,” it cannot be protected using conventional encryption methods. Biometric systems extract features from the biometric traits of the users and store them inside their databases as “biometric templates.” Even though the retina is the most accurate biometric characteristic known and is currently used for high-security identity verification, there exists no retinal recognition system that protects retinal templates. Mahshid and her colleagues are working to fill this gap, designing a retinal recognition system that protects the private information of its users. To achieve this aim, the biometric templates stored in the system’s database should be irreversible and unlinkable.

The research team developed a software system that can recognise individuals with high accuracy using their retinal images while protecting biometric information from privacy-invasion threats. Machine learning methods were applied to evaluate the system’s accuracy and the level of privacy protection; these evaluations demonstrated the proposed system achieves high recognition accuracy, resulting in a user-friendly system secure against hacking and identity theft.

In recognition of the quality and significance of her research, Mahshid Sadeghpour is the First Prize Winner in the Physical Sciences category for the Royal Society of Victoria's Young Scientist Research Prizes in 2022.