具有消息恢复的数字签名方案的一个注记

对具有消息恢复的数字签名方案提出了两种攻击方法.此外,对原方案进行了改进,通过对改进方案的安全性分析得出结论:改进方案比原方案更安全,并且消息恢复过程只需要计算一次大数模幂乘和两次单向函数.     

麦蚜天敌捕食强度的灰色评判

利用灰色局势决策理论,对两种麦蚜的优势种天敌作了灰色评判。结果表明,从捕食强度来看,小麦的孕穗期至腊熟期阶段,麦长管蚜与麦二叉蚜的优势种天敌依次为：龟纹瓢虫,草间小黑蛛和八斑球腹蛛。     

混合互补判断矩阵一致性研究

给出混合互补判断矩阵一致性的定义和判别加性一致性的方法.定义了核算子、核矩阵,对带有精确数、三角模糊数和梯形模糊数的混合互补判断矩阵给出基于核矩阵的一致性调整方法,调整量可以是精确数也可以是模糊数.最后给出一个应用实例.     

线性均衡约束最优化的一个广义投影强次可行方向法

本文讨论带线性均衡约束最优化问题,首先利用摄动技术和一个互补函数将问题等价转化为一般约束最优化问题,然后结合广义投影技术和强次可行方向法思想,建立了问题的一个新算法.算法在迭代过程中保证搜索方向不为零,从而使得每次迭代只需计算一次广义投影.在适当的条件下,证明了算法的全局收敛性,并对算法进行了初步的数值试验.     

Comments on ID-based multi-signature with distinguished signing authorities

A multi-signature scheme with distinguished signing authorities is a multi-signature scheme where the signed document is divided into several parts and each signer signs only on the part which he is responsible for. This article shows the security weakness of Wu–Hsu’s ID-based multi-signature scheme with distinguished signing authorities.     

Vectorial Approach to Fast Correlation Attacks

A new, vectorial approach to fast correlation attacks on binary memoryless combiners is proposed. Instead of individual input sequences or their linear combinations, the new attack is targeting subsets of input sequences as a whole thus exploiting the full correlation between the chosen subset and the output sequence. In particular, the set of all the input sequences can be chosen as the target. The attack is based on a novel iterative probabilistic algorithm which is also applicable to general memoryless combiners over finite fields or finite rings. To illustrate the effectiveness of the introduced approach, experimental results obtained for random balanced combining functions are presentedMost of this work was done while he was with Rome CryptoDesign Center, Gemplus, Italy     

模糊综合评价模型在教师评价中的应用

教师评价是教育评价的一个重要环节 ,我国教师评价的历史不长 ,所以目前尚未建立起科学的评价体系 ,由于教师评价的多因素性及评价因素的模糊性 ,可以用模糊数学建立综合评价模型 .     

一种基于图论与熵的专家判断客观可信度的确定方法

本文给出一种群决策中确定专家判断可信度的方法，其主要思路是首先通过图论中最小生成树的方法提取专家判断矩阵的全部信息，其次，使用相对熵指标确定获得专家判断的最终结果，并同时衡量专家自身判断的统一程度，从而确定专家判断的相对客观可信度。最后，文章给出一个典型的算例以说明该方法的可行性和有效性。     

On Weaknesses of Non–surjective Round Functions

We propose a new attack on Feistel ciphers with a non-surjective round function such as the CAST cipher family and LOKI91. We extend the attack towards block ciphers that use a non-uniformly distributed round function and apply the extended attack to the CAST family. This attack demonstrates that the round function of a Feistel cipher with six to eight rounds needs to be surjective and sufficiently uniform.     

Theorems of the Alternative and Duality

This paper investigates the relations between theorems of the alternative and the minimum norm duality theorem. A typical theorem of the alternative is associated with two systems of linear inequalities and/or equalities, a primal system and a dual one, asserting that either the primal system has a solution, or the dual system has a solution, but never both. On the other hand, the minimum norm duality theorem says that the minimum distance from a given point z to a convex set is equal to the maximum of the distances from z to the hyperplanes separating z and . We consider the theorems of Farkas, Gale, Gordan, and Motzkin, as well as new theorems that characterize the optimality conditions of discrete l ₁-approximation problems and multifacility location problems. It is shown that, with proper choices of , each of these theorems can be recast as a pair of dual problems: a primal steepest descent problem that resembles the original primal system, and a dual least–norm problem that resembles the original dual system. The norm that defines the least-norm problem is the dual norm with respect to that which defines the steepest descent problem. Moreover, let y solve the least norm problem and let r denote the corresponding residual vector. If r=0, which means that z , then y solves the dual system. Otherwise, when r0 and z , any dual vector of r solves both the steepest descent problem and the primal system. In other words, let x solve the steepest descent problem; then, r and x are aligned. These results hold for any norm on . If the norm is smooth and strictly convex, then there are explicit rules for retrieving x from r and vice versa.