TY - GEN
T1 - Speckle-based Optical Cryptosystem for Face Recognition
AU - Zhao, Qi
AU - Li, Huanhao
AU - Yu, Zhipeng
AU - Lai, Puxiang
N1 - Publisher Copyright:
© 2023 SPIE.
PY - 2023/3/15
Y1 - 2023/3/15
N2 - 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.
AB - 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.
KW - deep learning
KW - optical cryptosystem
KW - optical encryption
KW - speckle
UR - http://www.scopus.com/inward/record.url?scp=85159782549&partnerID=8YFLogxK
U2 - 10.1117/12.2645932
DO - 10.1117/12.2645932
M3 - Conference article published in proceeding or book
AN - SCOPUS:85159782549
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - AI and Optical Data Sciences IV
A2 - Jalali, Bahram
A2 - Kitayama, Ken-ichi
PB - SPIE
T2 - AI and Optical Data Sciences IV 2023
Y2 - 30 January 2023 through 2 February 2023
ER -