Registration and verification of biometric modalities using encryption techniques in a deep neural network

US11615176B2 · kind B2 · utility

Assignee

• Tata Consultancy Services Limited · IN

Inventors

• Arun Kumar Jindal · Pune, IN
• Imtiyazuddin Shaik · Hyderabad, IN
• Harika Narumanchi · Chennai, IN
• Vasudha Kumari · Pune, IN
• Srinivasa Rao Chalamala · Hyderabad, IN
• Rajan Mindigal Alasingara Bhattachar · Kanchinakote, IN
• Sachin Premsukh Lodha · Jamkhed, IN

Key dates

• Filing date: Sep 23, 2020
• Grant date: Mar 28, 2023
• Expiry date: May 15, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V40/53
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Conventionally, biometric template protection has been achieved to improve matching performance with high levels of security by use of deep convolution neural network models. However, such attempts have prominent security limitations mapping information of images to binary codes is stored in an unprotected form. Given this model and access to the stolen protected templates, the adversary can exploit the False Accept Rate (FAR) of the system. Secondly, once the server system is compromised all the users need to be re-enrolled again. Unlike conventional systems and approaches, present disclosure provides systems and methods that implement encrypted deep neural network(s) for biometric template protection for enrollment and verification wherein the encrypted deep neural network(s) is utilized for mapping feature vectors to a randomly generated binary code and a deep neural network model learnt is encrypted thus achieving security and privacy for data protection.