DeepSLM: Speckle‐Licensed Modulation via Deep Adversarial Learning for Authorized Optical Encryption and Decryption
Optical encryption is pivotal in information security, offering parallel processing, speed, and robust security. The simplicity and compatibility of speckle‐based cryptosystems have garnered considerable attention. Yet, the predictable statistical distribution of speckle optical fields’ characteristics can invite statistical attacks, undermining these encryption methods. The proposed solution, a deep adversarial learning‐based speckle modulation network (DeepSLM), disrupts the strong intercorrelation of speckle grains. Utilizing the unique encoding properties of speckle patterns, DeepSLM facilitates license editing within the modulation phase, pioneering a layered authentication encryption system. Our empirical studies confirm DeepSLM's superior performance on key metrics. Notably, the testing dataset reveals an average Pearson correlation coefficient above 0.97 between decrypted images and their original counterparts for intricate subjects like human faces, attesting to the method's high fidelity. This innovation marries adjustable modification, optical encryption, and deep learning to enforce tiered data access control, charting new paths for creating user‐specific access protocols.
Authors
- Yuandong Zheng (ORCID: https://orcid.org/0000-0002-8325-4318)
- Haofan Huang (ORCID: https://orcid.org/0000-0002-3505-9972)
- Puxiang Lai (ORCID: https://orcid.org/0000-0003-4811-2012)
- Huanhao Li (ORCID: https://orcid.org/0000-0002-1652-6328)
- Shengfu Cheng (ORCID: https://orcid.org/0000-0003-2757-6264)
- Tianting Zhong (ORCID: https://orcid.org/0000-0002-3925-5903)
- Chi Man Woo (ORCID: https://orcid.org/0000-0003-1653-5029)
- Qi Zhao (ORCID: https://orcid.org/0000-0002-8594-6940)
- Jie Tian (ORCID: https://orcid.org/0000-0003-0498-0432)
- Yuanjin Zheng (ORCID: https://orcid.org/0000-0001-5791-088X)
- Honglin Liu (ORCID: https://orcid.org/0000-0003-2473-9056)
- Zhipeng Yu (ORCID: https://orcid.org/0009-0000-1414-3801)
- Yi Gao (ORCID: https://orcid.org/0000-0003-0094-8136)
Institutions
- Hong Kong Polytechnic University (HK)
- Nanyang Technological University (SG)
- Shenzhen University (CN)
- Shenzhen Polytechnic University (CN)
- Chinese Academy of Sciences (CN)
- Shandong Institute of Automation (CN)
- Shanghai Institute of Optics and Fine Mechanics (CN)
- Beihang University (CN)
Publication Details
- Journal
- Advanced Intelligent Systems
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1002/aisy.202400150
- Citations
- 4
- Primary Topic
- Random lasers and scattering media
- Type
- article
- Field-Weighted Citation Impact
- 1.11
Funders
- National Natural Science Foundation of China
- Innovation and Technology Commission
- Hong Kong Polytechnic University
- Science, Technology and Innovation Commission of Shenzhen Municipality