Construction of a key-dependent message secure symmetric encryption scheme in the ideal cipher model

Key-dependent message （KDM） security is an important security issue that has attracted much research in recent years. In this paper, we present a new construction of the symmetric encryption scheme in the the ideal cipher model （ICM）; we prove that our scheme is KDM secure against active attacks with respect to arbitrary polynomialtime challenge functions. Our main idea is to introduce a universal hash function （UHF） h as a random value for each encrypfion, and then use s = h（sk） as the key of the ideal cipher F, where sk is the private key of our symmetric encryption scheme. Although many other schemes that are secure against KDM attacks have already been proposed, in both the ideal standard models, the much more significance of our paper is the simplicity in which we implement KDM security against active attacks.     

Gaussian sampling of lattices for cryptographic applications

Gaussian sampling is the major class of algorithms for solving the close vector problem(CVP)of lattices.In this paper we present a novel Gaussian sampling algorithm,which has the same cryptographic applications with original Gaussian sampling algorithms.Our novel Gaussian sampling algorithm has smaller deviations,meaning smaller space sizes of lattice based public-key ciphers.The shape of our novel algorithm is almost repeated implementations of original algorithm,with random repeating times.Major result is that the deviation can be reduced to 0.64～0.75 of that of original Gaussian sampling algorithm without clearly increasing the average time cost.     

轻量级分组密码算法DoT的模板攻击

模板攻击是一种重要的侧信道分析方法,其在实际密码算法破译中具有较强的区分能力。轻量级分组密码算法DoT在硬件和软件实现中都表现出优秀的性能,尽管目前针对DoT算法的传统数学攻击已经取得了一定效果,但是该算法在具体实现中是否足以抵御侧信道攻击仍有待研究。基于DoT算法结构及其S盒特点,提出一种针对DoT算法的模板攻击方法。基于汉明重量模型来刻画加密算法运行时的能耗特征,将S盒输出值的具体分布作为中间状态值构造区分器,从而进行密钥恢复。测试结果表明,该模板攻击仅需6组明文就可恢复出8 bit密钥信息,DoT密码算法在该模板攻击下具有脆弱性。     

求解0-1背包问题的混合贪婪遗传算法

求解0-1背包问题（KP）的最优解的时候,传统遗传算法（GA）的局部求精能力不足而简单局部搜索算法的全局探索能力有限,针对上述问题,将这两个算法整合并提出了混合贪婪遗传算法（HGGA）。在GA全局搜索框架下增加局部搜索模块,并改进传统仅基于物品价值密度的修复算子,增加基于物品价值的贪婪混合选项,从而加速寻优过程。HGGA一方面引导种群在进化的优质解空间中展开精细搜索,另一方面依靠GA的经典操作算子开拓全局搜索空间,从而达到算法求精能力和开拓能力的良好平衡。HGGA分别在三组数据上做了测试,结果表明在第一组15个测试用例中的12个上,HGGA能够百分百找到最优解,成功率达到80%;在第二组小规模数据集上,HGGA的性能明显好于其他同类GA和其他元启发算法;在第三组大规模数据集上,HGGA较其他元启发式算法具有更好的稳定性和高效性。     

改进蚁群优化算法求解折扣{0-1}背包问题

折扣{0-1}背包问题（Discounted {0-1} Knapsack Problem,DKP）是一个NP-困难的组合优化问题,尽管已经存在一些求解DKP的智能优化算法,但目前尚没有用蚁群优化（Ant Colony Optimization,ACO）算法求解DKP的研究。提出了一个求解DKP的改进ACO（Modified ACO,MACO）算法。MACO算法使用整数编码以保证每组物品最多只有一个物品被选中,在MACO算法构造解的每一步,采用组内竞争选择来降低算法的时间复杂性,对计算选择概率的公式,放弃启发式信息以减少参数并简化算法参数设置,对蚂蚁构造出的解,经修复后使用基于价值密度和价值的混合贪婪优化算子来提高算法的寻优能力。在四类测试用例上对MACO算法进行了测试并与其他算法进行比较,实验结果表明MACO算法的性能明显优于其他算法。     

轻量级分组密码GIFT的一种白盒实现方案

白盒实现是将已知的密码算法通过白盒密码技术进行设计,使其在白盒攻击环境中具有与原算法相同的功能,同时保证该算法的安全性不会遭到破坏。文章提出一种轻量级分组密码GIFT的白盒实现方案,该方案主要思想是使用查找表表示密码算法每轮的输入输出,并使用不同大小的仿射函数编码查找表的输入输出。该方案需要13.92 MB的内存空间,并能抵抗BGE攻击、MGH攻击、仿射等价算法攻击和差分矩阵攻击等代数分析攻击。其中,仿射等价算法攻击的复杂度大于O(2^82)。     

Method Based on Time Randomization to Resist Fault Sensitivity Analysis

A fault sensitivity analysis (FSA)-resistance model based on time randomization is proposed. The randomization unit is composed of two parts, namely the configurable register array (R-A) and the decoder (chiefly random number generator, RNG). In this way, registers chosen can be either valid or invalid depending on the configuration information generated by the decoder. Thus, the fault sensitivity information can be confusing. Meanwhile, based on this model, a defensive scheme is designed to resist both fault sensitivity analysis (FSA) and differential power analysis (DPA). This scheme is verified with our experiments.     

2n周期优秀二元序列生成及其特性分析简

The 2ⁿ-periodic binary sequence with high linear complexity and high k-error linear complexity is defined as an excellent sequence. We design a genetic algorithm for generating excellent sequences and studying their features. Choosing the N-periodic binary sequences, where N=8, 16, 32, k=N/4, we search the resulted sequences by the genetic algorithm with various parameters, and compute the linear complexity profiles of results sequences by using the Lauder-Paterson algorithm, to confirm that the obtained sequences are the real excellent sequences. By numerous experiments, we speculate that the k-error linear complexity of the N-periodic binary excellent sequence meets the formula LC_k(S)≤N-2k+1, when k=N/4、N/8 (we also do experiments on sequences with periods 64, 128 and 256). By the brute-force method we obtain that the proportion of the excellent sequence in all binary sequences of the same period is 1/4.     

基于最优区分器的多差分密码分析方法

如何利用多个差分特征对分组密码算法进行差分攻击,从而精确地估计出分组密码算法抵抗差分攻击的能力,是一个重要的研究课题.文中基于最优区分器的思想,提出了一种多差分密码分析方法.针对每个实验密钥,构造出基于多个差分特征的统计量,根据统计量的大小判决实验密钥是否为正确密钥.给出了多差分分析方法的计算复杂度,分析了正确密钥、错误密钥对应统计量的概率分布规律,并在此基础上给出了多差分分析方法的成功率和数据复杂度之间的关系.通过具体实例表明,在成功率相同的条件下,基于的差分特征越多,需要的数据复杂度越小.     

针对LBlock算法的踪迹驱动Cache攻击

LBlock是一种轻量级分组密码算法,其由于优秀的软硬件实现性能而备受关注。目前针对LBlock的安全性研究多侧重于抵御传统的数学攻击。缓存( Cache)攻击作为一种旁路攻击技术,已经被证实对密码算法的工程实现具有实际威胁,其中踪迹驱动Cache攻击分析所需样本少、分析效率高。为此,根据LBlock的算法结构及密钥输入特点,利用访问Cache过程中密码泄露的旁路信息,给出针对LBlock算法的踪迹驱动Cache攻击。分析结果表明,该攻击选择106个明文,经过约27.71次离线加密时间即可成功恢复LBlock的全部密钥。与LBlock侧信道立方攻击和具有Feistel结构的DES算法踪迹驱动Cache攻击相比,其攻击效果更明显。