利用光反馈半导体激光器产生的混沌激光作为随机数发生器的物理熵源,通过8位ADC将熵源信息转化为二进制码,并经后续差分运算处理改善其随机性,最终获得了1Gbit/s的随机数.所产生的随机数通过了NIST Special Publication 800-22的全部测...利用光反馈半导体激光器产生的混沌激光作为随机数发生器的物理熵源,通过8位ADC将熵源信息转化为二进制码,并经后续差分运算处理改善其随机性,最终获得了1Gbit/s的随机数.所产生的随机数通过了NIST Special Publication 800-22的全部测试项.展开更多
The random sequence generated by linear feedback shift register can’t meet the demand of unpredictability for secure paradigms. A combination logistic chaotic equation improves the linear property of LFSR and constru...The random sequence generated by linear feedback shift register can’t meet the demand of unpredictability for secure paradigms. A combination logistic chaotic equation improves the linear property of LFSR and constructs a novel random sequence generator with longer period and complex architecture. We present the detailed result of the statistical testing on generated bit sequences, done by very strict tests of randomness: the NIST suite tests, to detect the specific characteristic expected of truly random sequences. The results of NIST’s statistical tests show that our proposed method for generating random numbers has more efficient performance.展开更多
目的为了解决当前混沌图像加密技术忽略了随机序列产生的时间延迟现象,且难以克服其自身迭代的周期性,使其序列的自相关性不理想,导致密文安全性不佳等问题。方法引入级联耦合混沌半导体环形激光器,设计基于物理随机位生成器与混沌像素...目的为了解决当前混沌图像加密技术忽略了随机序列产生的时间延迟现象,且难以克服其自身迭代的周期性,使其序列的自相关性不理想,导致密文安全性不佳等问题。方法引入级联耦合混沌半导体环形激光器,设计基于物理随机位生成器与混沌像素交叉互换的图像加密算法。首先引入SHA-256散列函数,利用明文像素值,生成一个256位的密钥,并将其分割为一系列的8位子密钥;利用这些子密钥来计算Logistic-Sine复合映射的初始条件,以输出一组随机序列;根据混沌序列,定义像素交叉互换机制,对输入明文进行预处理,消除相邻像素之间的相关性;基于级联耦合混沌半导体环形激光器,充分利用其自身的时间延迟与交叉反馈的特性,设计物理随机位生成器,以同步输出考虑时间延迟的控制矩阵与随机位流;将Logistic-Sine复合映射输出的混沌序列转换为一个过渡矩阵,联合控制矩阵,定义像素混淆机制,彻底改变明文的像素位置;最后,利用随机位流,设计像素联系扩散函数,改变图像的像素值。结果实验结果显示,与当前混沌加密技术相比,所提算法具有更高的安全性与鲁棒性,能够有效抗击明文攻击,相应的密文熵值约为7.9958,且NPCR(7)Number of Pixel Change Rate(8)、UACI(Unified Average Changing Intensity)分别为99.50%、33.46%。结论所提加密算法具有较高的安全性和抗攻击能力,能够安全保护图像在网络中传输,在信息防伪等领域具有较好的应用价值。展开更多
Pseudo-Random Number Generators (PRNGs) are required for generating secret keys in cryptographic algorithms, generating sequences of packet in Network simulations (workload generators) and other applications in variou...Pseudo-Random Number Generators (PRNGs) are required for generating secret keys in cryptographic algorithms, generating sequences of packet in Network simulations (workload generators) and other applications in various fields. In this paper we will discuss a list of some requirements for generating a reliable random sequence and then will present some PRNG methods which are based on combinational chaotic logistic map. In the final section after a brief introduction to two statistical test packets, TestU01 and NIST suite tests, the PRNG methods which are presented in the fourth section will be appraised under these test packets and the results will be reported.展开更多
文摘The random sequence generated by linear feedback shift register can’t meet the demand of unpredictability for secure paradigms. A combination logistic chaotic equation improves the linear property of LFSR and constructs a novel random sequence generator with longer period and complex architecture. We present the detailed result of the statistical testing on generated bit sequences, done by very strict tests of randomness: the NIST suite tests, to detect the specific characteristic expected of truly random sequences. The results of NIST’s statistical tests show that our proposed method for generating random numbers has more efficient performance.
文摘目的为了解决当前混沌图像加密技术忽略了随机序列产生的时间延迟现象,且难以克服其自身迭代的周期性,使其序列的自相关性不理想,导致密文安全性不佳等问题。方法引入级联耦合混沌半导体环形激光器,设计基于物理随机位生成器与混沌像素交叉互换的图像加密算法。首先引入SHA-256散列函数,利用明文像素值,生成一个256位的密钥,并将其分割为一系列的8位子密钥;利用这些子密钥来计算Logistic-Sine复合映射的初始条件,以输出一组随机序列;根据混沌序列,定义像素交叉互换机制,对输入明文进行预处理,消除相邻像素之间的相关性;基于级联耦合混沌半导体环形激光器,充分利用其自身的时间延迟与交叉反馈的特性,设计物理随机位生成器,以同步输出考虑时间延迟的控制矩阵与随机位流;将Logistic-Sine复合映射输出的混沌序列转换为一个过渡矩阵,联合控制矩阵,定义像素混淆机制,彻底改变明文的像素位置;最后,利用随机位流,设计像素联系扩散函数,改变图像的像素值。结果实验结果显示,与当前混沌加密技术相比,所提算法具有更高的安全性与鲁棒性,能够有效抗击明文攻击,相应的密文熵值约为7.9958,且NPCR(7)Number of Pixel Change Rate(8)、UACI(Unified Average Changing Intensity)分别为99.50%、33.46%。结论所提加密算法具有较高的安全性和抗攻击能力,能够安全保护图像在网络中传输,在信息防伪等领域具有较好的应用价值。
文摘Pseudo-Random Number Generators (PRNGs) are required for generating secret keys in cryptographic algorithms, generating sequences of packet in Network simulations (workload generators) and other applications in various fields. In this paper we will discuss a list of some requirements for generating a reliable random sequence and then will present some PRNG methods which are based on combinational chaotic logistic map. In the final section after a brief introduction to two statistical test packets, TestU01 and NIST suite tests, the PRNG methods which are presented in the fourth section will be appraised under these test packets and the results will be reported.
