ToMAS: Torus-based secure multi-factor biometric authentication system.

Area of Science:

• Computer Science
• Cryptography
• Biometrics

Background:

• Biometric authentication offers convenience but poses significant privacy risks.
• Existing systems often lack robust security for sensitive biometric data.
• Need for secure and privacy-preserving identity verification methods is growing.

Purpose of the Study:

• To propose a Torus-based secure Multi-factor biometric Authentication System (ToMAS).
• To enhance privacy during biometric enrollment and authentication phases.
• To develop an efficient and scalable solution for large-scale deployments.

Main Methods:

• Implemented a multi-factor approach combining physiological traits and password secrets.
• Utilized fully homomorphic encryption (FHE) for secure computations on encrypted data.
• Introduced ciphertext packing and modified bootstrapping for efficient Hamming distance evaluation.

Main Results:

• ToMAS secures both enrollment and authentication using cryptographic protocols.
• Encrypted a 9600-bit biometric template into an 82KB ciphertext.
• Computed Hamming distance between encrypted templates in under one second with no accuracy loss.

Conclusions:

• ToMAS provides a privacy-preserving solution for biometric authentication.
• The system demonstrates efficiency and scalability for real-world applications.
• ToMAS effectively mitigates privacy concerns associated with widespread biometric adoption.