Speckle-based optical cryptosystem for face recognition

Abstract

Face recognition has been widely implemented in public places for security purposes. However, face photos are sensitive biometric data, and their privacy is a common concern, which often needs to be protected via cryptosystems. Popular software-based cryptosystems have limitations on short secret key lengths, posing a significant threat when facing high performance quantum computing. Recently, in order to achieve higher level security, hardware-based optical cryptosystems have been investigated. However, due to the complexity of optical system designs, it is difficult to integrate the extensively studied optical double random phase encryption into current face recognition systems. Speckle-based cryptosystems, on the contrary, affords high-level safety with high adaptivity, high speed, and low cost, using simpler optical setups. In this study, a speckle-based optical cryptosystem for face recognition is proposed, and encrypted face recognition is experimentally demonstrated. During encryption, a scattering ground glass is utilized as the only physical secret key with 17.2 gigabit length, so as to encrypt face images via random optical speckles at light speed. During decryption, a specially designed neural network is pre-trained to reconstruct face images from speckles with high fidelity, allowing for up to 98% accuracy in the subsequent face recognition process. Apart from face recognition, the proposed speckle-based optical cryptosystem can also be transferred to other high-security cryptosystems due to its high security, high adaptivity, fast speed, and low cost.