摘要
近些年来,压缩感知理论被广泛地应用于图像处理、医学成像、地质勘探以及人脸识别等领域的研究当中。归功于其压缩加密特性,一些基于压缩感知的密码方案被提出。相反地,本文基于常用的密码学本原(DES、AES以及M序列),构造压缩感知的测量矩阵。与传统的测量矩阵(如高斯矩阵、混沌矩阵)实验对比,结果表明提出的三种经典密码算法的输出序列可被用作压缩感知的测量矩阵。
In recent years,compressed sensing theory has been widely used in image processing,medical imaging,geological exploration and face recognition.Due to its compressed encryption characteristics,some cryptographic schemes based on compressed sensing have been proposed.On the contrary,the measurement matrices of compressed sensing are constructed based on the commonly used cryptographic primitives(DES,AES and M sequence)in this paper.Compared with the traditional measurement matrices(such as Gaussian matrix and chaotic matrix),the experimental results show that the output sequences of the three classical cryptographic algorithms can be used as the measurement matrices of compressed sensing.
作者
谢冬
郭东升
叶四军
XIE Dong;GUO Dong-sheng;YE Si-jun(School of Computer and Information,Anhui Normal University,Wuhu 241003,China;Management Committee of Anhui Xinwu Economic Development Zone,Wuhu 241000,China)
出处
《安徽师范大学学报（自然科学版）》
CAS
2020年第1期28-32,共5页
Journal of Anhui Normal University(Natural Science)
基金
国家自然科学基金青年科学基金项目(61801004)
安徽省自然科学基金青年项目(1808085QF211)
北京邮电大学重点实验室开放课题(SKLNST-2018-1-08)
安徽师范大学博士科研启动基金项目(751869)
作者简介
谢冬(1987—),男,安徽怀宁人,讲师,博士,主要从事密码学、压缩感知方向的研究.
