计算机科学
语义安全
加密
密文
辍学(神经网络)
像素
解码方法
基于属性的加密
理论计算机科学
算法
计算机安全
人工智能
公钥密码术
机器学习
作者
Xinrui Zhan,Chunli Zhu,Zhijie Gao,Shuai Wang,Qiang Jiao,Liheng Bian
出处
期刊:Optics Letters
[Optica Publishing Group]
日期:2022-11-01
卷期号:47 (23): 6169-6169
被引量:3
摘要
Single-pixel encryption is a recently developed encryption technique enabling the ciphertext amount to be decreased. It adopts modulation patterns as secret keys and uses reconstruction algorithms for image recovery in the decryption process, which are time-consuming and can easily be illegally deciphered if the patterns are exposed. We report an image-free single-pixel semantic encryption technique that significantly enhances security. The technique extracts semantic information directly from the ciphertext without image reconstruction, which significantly reduces computing resources for end-to-end real-time decoding. Moreover, we introduce a stochastic mismatch between keys and ciphertext, with random measurement shift and dropout, which effectively enhances the difficulty of illegal deciphering. Experiments on the MNIST dataset validate that 78 coupling measurements (0.1 sampling rate) with stochastic shift and random dropout achieved 97.43% semantic decryption accuracy. In the worst situation, when all the keys are illegally obtained by unauthorized attackers, only 10.80% accuracy can be achieved (39.47% in an ergodic manner).
科研通智能强力驱动
Strongly Powered by AbleSci AI