二进制序列的随机特性

1 引言在密码使用中,0、1序列(二元序列)常常需要从某种意义上呈现随机性。尤其是当一个二元序列在密码机中用作加密序列(密钥流或密钥序列)时,该序列必须近似随机。否则,密码分析人员就能够对密文运用统计技术进行破译,求得明文,从而大大削弱密码强度。假如二元序列确实近似于随机序列,那么利用统计办法分析密码将变得不可能。因此我们希望通过检验方式来决定一个序列是否近似随机。肯德尔和巴宾顿一史密     

随机数发生器检测与设计

随机数常作为密钥、初始化向量或密码协议中的时变参数,在密码应用中起到非常重要的作用。根据密码应用对随机性的要求,随机数生成器的输出序列必须满足随机性和不可预测性要求。文中分析了随机数生成器和伪随机数生成器两种生成器模型,给出了常用的随机性检测方法,以及可能的安全攻击方法,最后提出了一种随机性检测新方法。该方法基于输出样本的每比特的信息熵估计,可用于随机数发生器设计过程中的随机性评估。     

一类理想自相关序列的伪随机性

伪随机序列在流密码、信道编码、扩频通信等领域有着广泛的应用.线性复杂度及其稳定性是序列伪随机性的重要度量指标.C Ding等给出了一类具有理想自相关性的周期序列,该序列的0-1分布是几乎均衡的.本文讨论了此类序列的其它伪随机性.本文的主要结果如下:此类序列具有令人满意的线性复杂度;在一个符号替换之下此类序列的线性复杂度不会退化.     

单比特频数检测和块内频数检测的快速实现研究

随机序列在密码技术中占有非常重要的地位,随机性检测利用概率统计的方法对随机序列的随机性进行分析测试。美国国家标准与技术研究院(NIST)和我国国家密码管理局都发布了各自的随机性检测规范,二者都将单比特频数检测和块内频数检测作为其检测项。研究了单比特频数检测和块内频数检测的快速实现,提出了三种新的快速实现算法。这三种算法可以使单比特频数检测、块内频数检测和两种检测综合实现的速度分别提升29.2倍、15.5倍和32.8倍。     

分组密码算法的自相关检测参数选择

自相关检测是一种用以检测一个长度为n的二元序列与其左移d位后序列的关联程度的随机性检测算法.d的选择范围很大,对所有参数逐一进行检测不现实,需要研究检测参数之间的关系.定义了检测参数之间可能存在的3种关系,以分组长度为m的分组密码随机性检测为对象,综合考虑分组密码和自相关检测的特点,利用统计实验研究了自相关检测参数子集D={1,2,m/4,m/2,3m/4,m,2m}中参数的关系.研究结果表明,对分组密码进行自相关检测时,检测参数应该首选d=m.该方法和结果为研究其他类型密码算法的随机性检测参数选择提供了新思路.     

唯密文场景下的分组密码算法识别方法

唯密文场景下的分组密码算法识别方法研究,旨在探讨在仅知道密文的情况下,如何有效地识别出所使用的分组密码算法,这一问题的研究对于提高加密系统的安全性具有重要意义。通过对随机序列随机性检测方法的研究,基于集成学习模型构建了识别模型,实现了唯密文场景下的分组密码算法识别技术,可以有效提取密文数据特征,经实验验证,识别效果优于现有方法。     

一种基于网络的语音混沌加密算法

由于混沌同步问题,目前基于混沌的加密数据在网络中传送多采用TCP协议.文中针对网络中传输的数字语音数据,提出了一种数据分块加密算法,这种加密算法可以使用UDP协议传送密文数据,在一定程度上解决了部分密文丢失后接收端的解密问题.算法采用混沌模型库随机加密数据的方法,极大增强了混沌密码序列的随机性,克服了混沌序列加密大数据量数据时的序列周期问题,编程试验验证了这种算法的可行性.     

随机性测试的淘汰能力和相关性

随机数序列在密码学中有着至关重要的作用,实际应用中考虑到序列生成的时间和复杂度,通常使用的是存在某些缺陷的伪随机数序列,它们给密码系统带来了一定的风险性。因此,需要使用随机性测试来对生成的序列进行检验,NIST在一个测试包中收录了16个随机性测试,这是目前较为常用的测试包之一,它们相互间的关系及其优劣性一直是一个值得探讨的问题。     

混沌伪随机序列和数字语音保密通信

本文提出了对混沌数据进行适当处理产生伪随机序列用于数字语音保密通信的方法,并对该序列进行了抗破译能力分析及随机性测试。通过计算机模拟实验实现数字语音的保密通信,取得了满意的结果。     

混沌时间序列在密码学应用中的随机性测试

针对混沌时间序列的产生是否符合密码学应用中的序列随机性检测的要求，及随着参数变化对混沌时间序列的随机性检测的效果进行实验。实验表明混沌密码序列对随机性的测试的好坏存在不确定性，因此混沌序列应用到序列密码之前必须对序列进行随机性检测。     

Local randomness in pseudorandom sequences

The concept of provable cryptographic security for pseudorandom number generators that was introduced by Schnorr is investigated and extended. The cryptanalyst is assumed to have infinite computational resources and hence the security of the generators does not rely on any unproved hypothesis about the difficulty of solving a certain problem, but rather relies on the assumption that the number of bits of the generated sequence the enemy can access is limited. The concept of perfect local randomness of a sequence generator is introduced and investigated using some results from coding theory. The theoretical and practical cryptographic implications of this concept are discussed. Possible extensions of the concept of local randomness as well as some applications are proposed.A preliminary version of this paper was presented at Crypto '89, Santa Barbara, and will appear in the proceedings.     

一种基于四维混沌神经网络的通信数据加密算法

混沌神经网络序列具有带宽大、难于预测和重构等特点,因而非常适用于网络通信和数据加密.本文提出一种四维混沌神经网络序列的产生方法,利用四维混沌神经网络进行混合加密,所产生的二值序列对明文进行预处理.实验结果表明,该系统对产生的二值序列,具有良好的初值敏感度,序列随机性较为理想,同时,四维混沌神经网络大大增加了密钥空间,利...     

A novel design method for discrete time chaos based true random number generators

Discrete time chaos based true random number generators are lightweight cryptographic primitives that offer scalable performance for the emerging low power mobile applications. In this work, a novel design method for discrete time chaos based true random number generators is developed using skew tent map as a case study. Optimum parameter values yielding maximum randomness are calculated using a mathematical model of true random number generator. A practical information measure is used to determine the maximum allowable parameter variation limits. Appropriate mapping between dynamic system and circuit parameters is established and a current mode skew tent map circuit is designed to validate proposed method.     

基于序列密码的强PUF抗机器学习攻击方法

物理不可克隆函数(Physical Unclonable Function, PUF)在信息安全领域具有极其重要的应用前景,然而也存在其自身安全受机器学习攻击等方面的不足。该文通过对PUF电路和密码算法的研究,提出一种基于序列密码的强PUF抗机器学习攻击方法。首先,通过构造滚动密钥生成器产生随机密钥,并与输入激励进行混淆;然后,将混淆后的激励通过串并转换电路作用于强PUF,产生输出响应;最后,利用Python软件仿真和FPGA硬件实现,并分析其安全性和统计特性。实验结果表明,当建模所用激励响应对(Challenge Response Pairs, CRPs)高达106组时,基于逻辑回归、人工神经网络和支持向量机的攻击预测率接近50%的理想值。此外,该方法通用性强、硬件开销小,且不影响PUF的随机性、唯一性以及可靠性。     

Quasi-chaotic coding over GF(q)

In this paper, we present quasi-chaotic (QC) schemes for secure digital communication systems, designed over Galois fields (GFs) with optimal randomness properties. Schemes with the maximum-output sequence length (all-zero input response) are presented for different GFs. Two coefficients are used to quantitatively measure the proximity of the behavior of these schemes with respect to the ideal white noise behavior. The proposed schemes outperform those presented by Frey in his paper, and achieve the optimal QC properties available for a given chaotic digital scheme. The proposed schemes have also a very little loss in bit-error rate performance so that they are a good alternative to the design of systems for which encryption and error correction are important joint goals. They can be implemented with time-variant coefficients in order to highly improve the cryptographic properties of the transmission.     

Highly dispersive substitution box (S‐box) design using chaos

Highly dispersive S‐boxes are desirable in cryptosystems as nonlinear confusion sub‐layers for resisting modern attacks. For a near optimal cryptosystem resistant to modern cryptanalysis, a highly nonlinear and low differential probability (DP) value is required. We propose a method based on a piecewise linear chaotic map (PWLCM) with optimization conditions. Thus, the linear propagation of information in a cryptosystem appearing as a high DP during differential cryptanalysis of an S‐box is minimized. While mapping from the chaotic trajectory to integer domain, a randomness test is performed that justifies the nonlinear behavior of the highly dispersive and nonlinear chaotic S‐box. The proposed scheme is vetted using well‐established cryptographic performance criteria. The proposed S‐box meets the cryptographic performance criteria and further minimizes the differential propagation justified by the low DP value. The suitability of the proposed S‐box is also tested using an image encryption algorithm. Results show that the proposed S‐box as a confusion component entails a high level of security and improves resistance against all known attacks.     

Extracting randomness from multiple independent sources

We study the problem of deterministically extracting almost perfect random bits from multiple weakly random sources that are mutually independent. With two independent sources, we have an explicit extractor which can extract a number of random bits that matches the best construction currently known, via the generalized leftover hash lemma. We also extend our construction to extract randomness from more independent sources. One nice feature is that the extractor still works even with all but one source exposed. Finally, we apply our extractor for a cryptographic task in which a group of parties wants to agree on a secret key for group communication over an insecure channel, without using ideal local randomness.     

一种混合混沌序列的研究

针对单一混沌映射产生的序列复杂度比较低的缺点,提出一种新的混合混沌序列产生方法。该方法主要是通过组合不同的混沌映射并且扰动混沌映射中的参数来产生混沌序列。对产生的序列进行了平衡性、随机性和相关性等分析,并将该序列作为扩频码用于直接序列扩频系统中进行仿真。仿真结果表明,这种混合混沌序列有较好的平衡性、随机性和相关性,证明了该序列作为扩频码的可行性。     

“串行检验”比较于传统的随机性检验方法的优越性

随机序列在密码学中占有重要的地位。2001年3月NIST公布了16种检验序列随机性的标准方法，其中没有包括传统的序偶检验和扑克检验，有关方面只列出了一个所谓“串行检验”的方法。说明串行检验其实优于同时使用扑克检验和序偶检验的效果，因此它才完全取代传统的有关检验方法而出现于NIST的上述标准中。