A Comparative Assessment of Homomorphic Encryption Algorithms Applied to Biometric Information

Abstract

This paper provides preliminary research regarding the implementation and evaluation of a hybrid mechanism of authentication based on fingerprint recognition interconnected with RFID technology, using Arduino modules, that can be deployed in different scenarios, including secret classified networks. To improve security, increase efficiency, and enhance convenience in the process of authentication, we perform a comparative assessment between two homomorphic encryption algorithms, the Paillier partial homomorphic algorithm and the Brakerski–Gentry–Vaikuntanathan fully homomorphic encryption scheme, applied to biometric templates extracted from the device mentioned above, by analyzing factors such as a histogram analysis, mean squared error (MSE), peak signal-to-noise ratio (PSNR), the structural similarity index measure (SSIM), the number of pixel change rate (NPCR), the unified average changing intensity (UACI), the correlation coefficient, and average encryption time and dimension. From security and privacy perspectives, the present findings suggest that the designed mechanism represents a reliable and low-cost authentication alternative that can facilitate secure access to computer systems and networks and minimize the risk of unauthorized access.

Preliminary Experiments of a Real-World Authentication Mechanism Based on Facial Recognition and Fully Homomorphic Encryption

“…In the last phase, decryption implies the existence of a ciphertext (ct) that needs to be decrypted, using a private key (sk) from which the original message is obtained: Decrypt(ct, sk) → pt. Another important step described by [56] includes the evaluation of the homomorphic circuit that encompasses the development of a supplementary function over the ciphertexts (ct 1 , ct 2 ) without seeing the messages (pt 1 , pt 2 ), which takes ciphertexts as input points from which the evaluated ciphertexts result. The encryption scheme comprises four main operations, namely KeyGen, Encrypt, Decrypt, Evaluate, for circuit C, considering the input parameter t, the encryption key pair (sk, pk) generated via the KeyGen function, the plaintext messages pt = (pt 1 , pt 2 .…”

Enhancing reservoir computing for secure digital image encryption using finance model forecasting

“…The main goal is to assess how well reservoir computing techniques for encrypting and decrypting digital images increase security safeguards against potential attackers. Reservoir computing is not limited to picture encryption; it may also improve financial prediction accuracy by integrating hyperchaotic models into this framework (Crihan et al, 2023).…”