4.6 Article

Embedding cryptographic features in compressive sensing

期刊

NEUROCOMPUTING
卷 205, 期 -, 页码 472-480

出版社

ELSEVIER
DOI: 10.1016/j.neucom.2016.04.053

关键词

Secure compressive sensing; Symmetric-key cipher; Parallel compressive sensing; Random permutation

资金

  1. National Natural Science Foundation of China [61502399, 61402547, 61502314, 61403313, 61572089]
  2. Natural Science Foundation Project of Chongqing CSTC [cstc2015jcyjA40039]
  3. Fundamental Research Funds for the Central Universities [XDJK2015C077]
  4. Macau Science and Technology Development Fund [FDCT/009/2013/A1, FDCT/046/2014/A1]
  5. Research Committee at University of Macau [MRG007/ZJT/2015/FST, MRG021/ZJT/2013/FST, MYRG2014-00031-FST, MYRG2015-00056-FST]

向作者/读者索取更多资源

Compressive sensing (CS) has been widely studied and applied in many fields. Recently, the way to perform secure compressive sensing (SCS) has become a topic of growing interest. The existing works on SCS usually take the sensing matrix as a key and can only be considered as preliminary explorations on SCS. In this paper, we firstly propose some possible encryption models for CS. It is believed that these models will provide a new point of view and stimulate further research in both CS and cryptography. Then, we demonstrate that random permutation is an acceptable permutation with overwhelming probability, which can effectively relax the Restricted Isometry Constant for parallel compressive sensing. Moreover, random permutation is utilized to design a secure parallel compressive sensing scheme. Security analysis indicates that the proposed scheme can achieve the asymptotic spherical secrecy. Meanwhile, the realization of chaos is used to validate the feasibility of one of the proposed encryption models for CS. Lastly, results verify that the embedding random permutation based encryption enhances the compression performance and the scheme possesses high transmission robustness against additive white Gaussian noise and cropping attack. (C) 2016 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据