Dual Image Cryptosystem Using Henon Map and Discrete Fourier Transform

This paper introduces an efficient image cryptography system.The pro-posed image cryptography system is based on employing the two-dimensional(2D)chaotic henon map(CHM)in the Discrete Fourier Transform(DFT).The proposed DFT-based CHM image cryptography has two procedures which are the encryption and decryption procedures.In the proposed DFT-based CHM image cryptography,the confusion is employed using the CHM while the diffu-sion is realized using the DFT.So,the proposed DFT-based CHM image crypto-graphy achieves both confusion and diffusion characteristics.The encryption procedure starts by applying the DFT on the image then the DFT transformed image is scrambled using the CHM and the inverse DFT is applied to get the final-ly encrypted image.The decryption procedure follows the inverse procedure of encryption.The proposed DFT-based CHM image cryptography system is exam-ined using a set of security tests like statistical tests,entropy tests,differential tests,and sensitivity tests.The obtained results confirm and ensure the superiority of the proposed DFT-based CHM image cryptography system.These outcomes encourage the employment of the proposed DFT-based CHM image cryptography system in real-time image and video applications.

Robust Multi-Watermarking Algorithm for Medical Images Based on GoogLeNet and Henon Map

The field of medical images has been rapidly evolving since the advent of the digital medical information era.However,medical data is susceptible to leaks and hacks during transmission.This paper proposed a robust multi-watermarking algorithm for medical images based on GoogLeNet transfer learning to protect the privacy of patient data during transmission and storage,as well as to increase the resistance to geometric attacks and the capacity of embedded watermarks of watermarking algorithms.First,a pre-trained GoogLeNet network is used in this paper,based on which the parameters of several previous layers of the network are fixed and the network is fine-tuned for the constructed medical dataset,so that the pre-trained network can further learn the deep convolutional features in the medical dataset,and then the trained network is used to extract the stable feature vectors of medical images.Then,a two-dimensional Henon chaos encryption technique,which is more sensitive to initial values,is used to encrypt multiple different types of watermarked private information.Finally,the feature vector of the image is logically operated with the encrypted multiple watermark information,and the obtained key is stored in a third party,thus achieving zero watermark embedding and blind extraction.The experimental results confirmthe robustness of the algorithm from the perspective ofmultiple types of watermarks,while also demonstrating the successful embedding ofmultiple watermarks for medical images,and show that the algorithm is more resistant to geometric attacks than some conventional watermarking algorithms.

A Chaotic Pulse Train Generator Based on Henon Map

The Henon map forms one of the most-studied two-dimensional discrete-time dynamical systems that exhibits chaotic behavior.The Henon map takes a point(Xn,Yn)in the plane and maps it to a new point(Xn+1,Yn+1).In this paper,a chaotic pulse generator based on the chaotic Henon map is proposed.It consists of a Henon map function subcircuit to realize the Henon map and another subcircuit to perform the iterative operation.The Henon map subcircuit comprises operational amplifiers,multipliers,delay elements and resistors,whereas,the iterative subcircuit is implemented with a simple design that comprises of an edge forming circuit followed by a monostable multivibrator and a voltage controlled switch without the use of any clock control.The proposed design can be used to realize the Henon map and also to generate a chaotic pulse train,with a controllable time interval and pulse position.The proposed circuit is implemented and simulated using Multisim 13.0 and MATLAB R2019b.The chaotic nature of the generated pulse train and also the time interval between the consecutive pulses is verified by the calculation of its Lyapunov exponents.

Hash function based on the generalized Henon map

A new Hash function based on the generalized Henon map is proposed. We have obtained a binary sequence with excellent pseudo-random characteristics through improving the sequence generated by the generalized Henon map, and use it to construct Hash function. First we divide the message into groups, and then carry out the Xor operation between the ASCII value of each group and the binary sequence, the result can be used as the initial values of the next loop. Repeat the procedure until all the groups have been processed, and the final binary sequence is the Hash value. In the scheme, the initial values of the generalized Henon map are used as the secret key and the messages are mapped to Hash values with a designated length. Simulation results show that the proposed scheme has strong diffusion and confusion capability, good collision resistance, large key space, extreme sensitivity to message and secret key, and it is easy to be realized and extended.

Discrete Chaos in Fractional Henon Map

In this study, a discrete fractional Henon map is proposed in the Caputo discrete delta’s sense. The results show that the discrete fractional calculus is an efficient tool and the maps derived in this way have simpler forms but hold rich dynamical behaviors.

分数阶忆阻Henon映射的可控多稳定性及其视频加密应用

基于局部有源离散忆阻器构建一种能够产生任意数量共存吸引子的分数阶忆阻Henon映射.该映射的不动点数量由忆阻器内部参数控制,实现可控的同质多稳定性,适合基于混沌的工程应用.通过相图、分岔图、最大Lyapunov指数和吸引盆等方法揭示该映射的复杂动力学行为.数值模拟结果表明,该分数阶映射能够产生各种周期轨道、混沌吸引子和倍周期分岔等现象.随后使用ARM数字平台实现该系统,实验结果验证其物理可实现性.最后,基于该映射设计一种视频加密算法,并通过安全性分析验证该加密算法能够有效保证视频的安全传输.

基于耦合的Henon和Sine映射及彩色图像加密

针对现有混沌映射模型的混沌空间小及混沌能力弱的问题,通过耦合二维Henon混沌映射模型和Sine混沌映射模型,设计一种新的二维混沌映射模型,通过耦合Sine混沌映射模型和Logistic混沌映射模型,设计一种新的一维混沌映射模型。针对使用单一置乱方法进行图像加密时安全性能不高的问题,通过使用Lorenz映射设计一种随机选择置乱算法的方法。使用设计的两种混沌映射及置乱选择方法,提出一种彩色图像加密方案。仿真实验结果表明:所提方法具有较大的置乱范围、较高的安全性和良好的图像加密效果,对常见的攻击有较强的抵抗力,且易于实现。

Pseudo-random sequence generator based on the generalized Henon map

By analysis and comparison of several chaotic systems that are applied to generate pseudo-random sequence, the generalized Henon map is proposed as a pseudo-random sequence generator. A new algorithm is created to solve the problem of non-uniform distribution of the sequence generated by the generalized Henon map. First, move the decimal point of elements in the sequence to the fight; then, cut off the integer; and finally, quantify it into a binary sequence. Statistical test, security analysis, and the application of image encryption have strongly supported the good random statistical characteristics, high linear complexity, large key space, and great sensitivity of the binary sequence.

一种基于混沌系统及Henon映射的快速图像加密算法

提出一种新的基于混沌系统及Henon映射的图像加密算法·使用经过取模处理的可逆二维非线性Henon映射对各像素点的灰度值进行链式循环迭代,每个迭代环节中Henon映射的参数与迭代次数依次取自一维混沌映射生成的混沌序列·该算法设计简单、运算快速、解密准确,尤其是解决了基于混沌或非线性变换的加密算法中普遍存在的由于计算机的有限精度或各计算机精度不同所导致的解密失败的难题,避免了常用置乱变换算法固有的缺陷及密码强度的不足,具有很高的安全性·

基于Henon映射的加密遥感图像的安全检索方案

遥感图像具有多时相、多语义、多波段等特点,鉴于遥感图像在商业行业及国防军事中的重要性,海量遥感图像密文检索的效率和精度直接影响了遥感大数据使用的广泛性和实时性.对密文存储的遥感大数据的安全检索,是其可用性最重要的标志之一.提出了一种基于Henon映射的遥感图像可搜索加密方案,根据遥感图像的成像原理及多波段特征,采用改进的Henon映射对每个波段的灰度值进行加密处理.同时,根据遥感图像的"大数据"特征,通过统计灰度值的区间信息来构造遥感图像的特征向量,并根据相似度匹配算法来检索目标图像.通过对Landsat 8遥感图像进行加密与检索进行实验,结果表明,该方案有效地提高了检索密文遥感图像的安全性及准确性,且计算复杂度低、通信成本开销小.

基于激光散斑和Henon映射的图像加密方法

为了提高图像在信息交换中的安全性与可靠性,提出一种将激光散斑和Henon映射混合应用于图像加密的新方法。激光散斑图像灰度分布具有随机性,采用SCAN语言将其扫描为不同的随机序列,该序列与Henon映射生成的序列求和形成新序列,新序列与待加密的原始图像按位异或实现加密。结果表明:该方法具有较好的加密效果,较强的密钥敏感性,较弱的相邻像素相关性,可抵御统计分析攻击。

基于约瑟夫和Henon映射的比特位图像加密算法

针对传统的图像加密算法,加密策略与待加密图像无关且对像素的置换和混淆往往被拆分为两个耦合性较低的孤立环节所带来的安全问题,提出基于约瑟夫遍历和广义Henon映射的图像比特位加密算法,将待加密图像安全哈希算法1(SHA-1)摘要和用户选定的加密参数联合作为密钥,驱动广义Henon映射对改进的用于位点置换的约瑟夫遍历映射的起始位置、报数间隔和报数方向进行随机扰动,从而使不同的加密图像和加密参数实质对应于不同的位点置换过程,并添加了位点混淆过程以提高位点置换的安全性。实验表明,所提算法可有效地抵抗选择性明文攻击,具有较大的密钥空间和较好的加密性能。

一种基于Henon映射的图像加密算法的分析及改进

该文对一种基于Henon映射的快速图像加密算法进行了分析,指出该算法存在明文敏感性不足和像素点逐个处理的问题。进而提出了一种改进的图像加密算法。改进算法将原算法的单点链接方式变成双点链接方式,从而获得了更好的扩散效果和更高的计算效率。实验仿真结果表明,改进的算法在安全性和加解密速度方面均有更好的表现。

一种结合Cat映射和Henon映射的图像加密技术

利用经典的Arnoldcat映射通过迭代虽然可以改变图像各像素点的位置,达到加密的目的,但由于Arnoldcat映射具有周期性的特点,经过一定次数的迭代后可以恢复原始图像,给系统带来了一定的安全隐患。把经过Arnoldcat映射置乱的图像注入Henon映射的混沌系统中,在位置置乱的基础上再进行像素值置乱,充分打乱图像的像素相关性,有效地避免了这一缺点。仿真结果表明,该算法可以达到较好的加密效果,并且具有较强的抗攻击性能。

一种基于Henon映射和Feistel结构的分组密码算法研究

混沌序列具有对初值和系统参数敏感等特点,因此非常适合应用于信息加密。本文在详细分析Henon映射的混沌和密码学特性的基础上,提出一种基于Feistel结构和Henon映射混沌分组密码算法,该算法最大的优点加密的轮次和子密钥的构造是基于混沌系统动态更新的,通过子密钥的动态生成,密码系统的随机性、复杂性得到了极大的提高。同时理论和实验表明,该算法具有较高的安全性,能够抵抗差分和线性密码分析。

基于广义Henon映射以及CNN超混沌系统图像加密方案

基于广义五阶Henon映射以及五阶细胞神经网络系统所产生的超混沌现象,设计了图像加密方案.首先利用五阶Henon映射产生超混沌序列X,将其作为细胞神经网络系统的初始条件,再产生另一超混沌序列Y,随机序列Y和原始图像经过变换生成密文图像.在此基础上进行了模拟仿真实验,并对图像密文熵、相关性和直方图以及密钥空间和敏感性等统计特性进行分析,结果表明:该算法图像加密抗攻击性强,安全性好,适于在网络中传播.

基于MapReduce的并行混合混沌加密方案

为了解决云环境中大数据量加密速度慢的问题,针对云计算环境中多节点的特点,结合混沌加密和MapReduce并行框架,提出一种并行混合混沌加密方案。通过对明文数据进行分组,在分组加密初始化时,混合三维Lorenz混沌系统和Chen混沌系统产生用于加密混沌系统的初值和干扰值,在加密过程中再次混合Henon映射和2D Logistic混沌映射,通过产生的混沌序列和干扰值对明文进行加密。实验结果表明,基于MapReduce的并行混合混沌加密技术能够在96个核的集群中提升360%的加密速度,减少81.2%的加密时间。

关于Henon映射的参数分布

本文报道了应用ＰＣ机大量迭代计算得到的Ｈｅｎｏｎ映射的参数分布图，参数取值为１．１≤ａ≤１．５、－０．４≤ｂ≤－０．２．根据混沌动力学的理论对所得到的结果从几个方面进行了分析比较，给出了一些解释．

基于Henon映射与改进的提升小波变换图像加密算法

数据在开放的网络环境中传输容易被盗取或破坏,因此常常利用混沌系统结合各种算法对多媒体数据进行加密。针对传统置乱扩散结构安全性低、依赖大量伪随机数的问题,文章提出一种基于Henon映射和改进的提升小波变换图像加密算法。首先,该算法对混沌系统产生的伪随机序列进行循环移位以及S盒处理生成密钥,同时将普通明文图像变换成一维奇偶索引序列;其次,将变换后的序列进行预测和更新处理,得到图像的低频近似分量和高频细节分量,完成一次加密;最后,分别翻转这两个被扰乱的分量,并再次执行预测和更新算法,完成对图像的加密。灰度图像上的计算机仿真实验与性能分析表明,使用该算法加密的图像失去了明显的统计特性,可以抵抗统计性攻击,有效提高了图像加密的安全性。

基于逻辑自映射的变尺度Henon搜索蜂群算法

鉴于Henon映射的自组织特性,提出基于Henon映射变尺度搜索的蜂群优化算法,通过Henon映射的逻辑自组织映射能力,在蜂群寻优搜索到的引领蜂群扰动附近的自组织变尺度搜索更优特征解,同时对这搜索范围进行变尺度动态调整收缩。最后将蜂群仿生优化算法应用到强干扰瑞利分布色噪声下微弱信号检测仿真实验和应用中,仿真实验表明,改进的蜂群优化算法显著提高了优化性能,寻优检测精度更高,并能实现全局快速收敛,能有效对强干扰下的微弱信号进行有效检测,检测性能提高显著。