随着云计算平台的普及,数据的加密往往在诸多数据处理之前进行,使加密域信号处理的研究受到越来越多的关注。首先从加密和压缩两方面同时入手,提出一种针对图像数据的高安全性加密算法,以及配套的加密图像压缩算法。突破加密信号难以压缩的瓶颈,取得与现有非加密域压缩方法非常接近的压缩效率。以构建实际系统的方式,论证了信息论中加密域和非加密域信号压缩效率可做到近似一致的观点;此外,针对很多应用场景中不能选择定制的加密算法,只能使用经典加密算法如RC4或AES的情况,申请人设计一套灵活、高效的可伸缩流密码加密图像压缩系统。在加密域利用基础层的可压缩性指导增强层在加密域的编码。使得用户可根据带宽条件和图像质量需求定制码流。在压缩效率和图像重构质量方面优于现有算法;提出一种高效的加密域可逆信息隐藏算法,摒弃了传统算法中对额外嵌入密钥的需求,大幅降低密钥协商的复杂度。在解码端,提出一种新型的SVM分类器来区分加密块和非加密块。在取得非常高的嵌入量的同时,亦保障原始图像的近无损恢复;此外,结合安全相似搜索、非局部均值降噪、Yao的混淆电路,构建了加密域的高性能去噪系统,取得了和非加密域非常近似的去噪性能。

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相關文章

[1] J. Duan, J. T. Zhou, and Y. M. Li, “Secure and Verifiable Outsourcing of Large-scale Nonnegative Matrix Factorization (NMF)”, Accepted in IEEE Trans. on Services Computing (T-SC), 2019.

[2] Y. F. Zheng, H. Y. Duan, X. T. Tang, C. Wang, and J. T. Zhou, “Denoising in the Dark: Privacy-Preserving Deep Neural Network Based Image Denoising”, Accepted in IEEE Trans. on Dependable and Secure Computing (T-DSC), 2019.

[3] Y. S. Zhang, J. T. Zhou, Y. Xiang, Y. Zhang, F. Chen, S. N. Pang, and X. F. Liao, “Computation Outsourcing Meets Lossy Channel: Secure Sparse Robustness Decoding Service in Multi-Clouds,” Accepted in IEEE Trans. on Big Data (T-BD), 2018.

[4] Y. M. Li and J. T. Zhou, “Fast and Effective Image Copy-Move Forgery Detection via Hierarchical Feature Point Matching”, IEEE Trans. on Inf. Forensics and Security (T-IFS), vol. 14, no. 5, pp. 1307-1322, 2019.

[5] J. T. Zhou, W. W. Sun, L. Dong, X. M. Liu, O. C. Au, and Y. Y. Tang, “Secure Reversible Image Data Hiding over Encrypted Domain via Key Modulation”, IEEE Trans. on Circuits and Syst. for Video Technology (T-CSVT), vol. 26, no. 3, pp. 441-452, 2016.

[6] J. T. Zhou, O. C. Au, G. T. Zhai, Y. Y. Tang, and X. M. Liu, “Scalable Compression of Stream Cipher Encrypted Images through Context-Adaptive Sampling”, IEEE Trans. on Inf. Forensics and Security (T-IFS), vol. 9, no.11, pp. 1857-1868, 2014.

[7] J. T. Zhou, X. M. Liu, O. C. Au, and Y. Y. Tang, “Designing an Efficient Image Encryption-then-Compression System via Prediction Error Clustering and Random Permutation”, IEEE Trans. on Inf. Forensics and Security (T-IFS), vol. 9, no. 2, pp. 39-50, 2014.

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