Santha-Vazirani sources,deterministic condensers and very strong extractors

Theory of Computing Systems - The notion of semi-random sources, also known as Santha-Vazirani (SV) sources, stands for a sequence of n bits, where the dependence of the i’th bit on the...     

具有直线提取器的匿名指纹方案

迄今为止,基于群签名构造匿名指纹方案的问题尚未得到较好地解决。为此,提出一个具有直线提取器的匿名指纹方案,新方案的设计过程使用了关于OR逻辑的Canard-Gouget-Hufschmitt知识证明技术(CANARD S, GOUGET A, HUFSCHMITT E. A handy multi-coupon system. ACNS 2006: Proceedings of the 4th International Conference on Applied Cryptography and Network Security, LNCS 3989. Berlin: Springer-Verlag, 2006: 66-81),Chida-Yamamoto批量零知识证明与验证技术(CHIDA K, YAMAMOTO G. Batch processing for proofs of partial knowledge and its applications. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2008, E91-A(1): 150-159)以及Arita(ARITA S. A straight-line extractable non-malleable commitment scheme. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2007, E90-A(7): 1384-1394)的直线可提取的承诺方案。需要指出的是,新方案支持并发注册,因此特别适合于基于互联网的应用环境。此外,新方案具有直线提取器,使得安全性证明中的归约算法无需依赖于低效的重绕策略,从而实现了紧密的安全性归约。形式化的安全性分析表明,新方案满足匿名指纹方案要求的所有性质。     

Constant-round zero-knowledge proofs of knowledge with strict polynomial-time extractors for NP

Barak and Lindell showed that there exist constant-round zero-knowledge arguments of knowledge with strict polynomial-time extractors.This leaves the open problem of whether it is possible to obtain an analogous result regarding constant-round zero-knowledge proofs of knowledge for NP.This paper focuses on this problem and gives a positive answer by presenting a construction of constant-round zero-knowledge proofs of knowledge with strict polynomial-time extractors for NP.     

具有在线提取器的成员基于身份的群签名方案

基于身份的群签名方案（ID-based GS）在本质上是追踪机制得到优化的群签名方案。ID-based GS方案的优势是对用户的成员公钥及其公开识别信息（如IP地址）进行了紧密的绑定。然而,已有的ID-based GS方案并不令人满意,这主要体现在无法在形式化的安全模型下得到证明,仅实现了放宽的安全性质,以及效率不高。通过结合双线性群上的消息块签名方案以及具有在线提取器的非交互知识证明技术,提出一个更为实用的ID-based GS方案。新方案具备两个显著的性质,即打开权威可以独立地打开争议的签名,而且注册协议能够以并发方式执行。此外,利用迭代散列函数和批验证技术,可以进一步地降低新方案的运算耗费。     

Comparative analysis of simple facial features extractors

In the article a certain class of feature extractors for face recognition is presented. The extraction is based on simple approaches: image scaling with pixel concatenation into a feature vector, selection of a small number of points from the face area, face image’s spectrum, and finally pixel intensities histogram. The experiments performed on several facial image databases (BioID [4], ORL face database [27], FERET [30]) show that face recognition using this class of extractors is particularly efficient and fast, and can have straightforward implementations in software and hardware systems. They can also be used in fast face recognition system involving feature-integration, as well as a tool for similar faces retrieval in 2-tier systems (as initial processing, before exact face recognition).

Deterministic Sampling Algorithms for Network Design

For several NP-hard network design problems, the best known approximation algorithms are remarkably simple randomized algorithms called Sample-Augment algorithms in Gupta et al. (J. ACM 54(3):11, 2007). The algorithms draw a random sample from the input, solve a certain subproblem on the random sample, and augment the solution for the subproblem to a solution for the original problem. We give a general framework that allows us to derandomize most Sample-Augment algorithms, i.e. to specify a specific sample for which the cost of the solution created by the Sample-Augment algorithm is at most a constant factor away from optimal. Our approach allows us to give deterministic versions of the Sample-Augment algorithms for the connected facility location problem, in which the open facilities need to be connected by either a tree or a tour, the virtual private network design problem, 2-stage rooted stochastic Steiner tree problem with independent decisions, the a priori traveling salesman problem and the single sink buy-at-bulk problem. This partially answers an open question posed in Gupta et al. (J. ACM 54(3):11, 2007).     

Cooperative Tasking for Deterministic Specification Automata

This paper proposes necessary and sufficient conditions for task decomposability with respect to an arbitrary finite number of agents. It is furthermore shown that fulfilling the decomposed local tasks by individual agents guarantees the satisfaction of the original global decomposable task. A divide‐and‐conquer approach for cooperative tasking among multi‐agent systems is proposed. The basic idea is to decompose an assigned global specification (given as a deterministic automaton) into subtasks for individual concurrent agents such that the fulfillment of these subtasks by each individual agent leads to the satisfaction of the global specification as a team. A cooperative scenario involving three robots has been implemented to illustrate the proposed technique. This work provides insights into what kinds of tasks can be achieved distributively, which helps designers specify achievable global tasks for a group of agents and design necessary information sharing among each other for a particular task.     

Deterministic asynchronous automata for infinite traces

This paper shows the equivalence between the family of recognizable languages over infinite traces and the family of languages which are recognized by deterministic asynchronous cellular Muller automata. We thus give a proper generalization of McNaughton's Theorem from infinite words to infinite traces. Thereby we solve one of the main open problems in this field. As a special case we obtain that every closed (w.r.t. the independence relation) word language is accepted by someI-diamond deterministic Muller automaton.This research has been supported by the ESPRIT Basic Research Action No. 6317 ASMICS 2.     

Deterministic global optimization for FNN training

This paper addresses the issue of training feedforward neural networks by global optimization. The main contributions include characterization of global optimality of a network error function, and formulation of a global descent algorithm to solve the network training problem. A network with a single hidden-layer and a single-output unit is considered. By means of a monotonic transformation, a sufficient condition for global optimality of a network error function is presented. Based on this, a penalty-based algorithm is derived directing the search towards possible regions containing the global minima. Numerical comparison with benchmark problems from the neural network literature shows superiority of the proposed algorithm over some local methods, in terms of the percentage of trials attaining the desired solutions. The algorithm is also shown to be effective for several pattern recognition problems.     

Deterministic inventory model for recycling system

An important new trend in supply chain management is repair, remanufacturing, recycling, or reuse of products collected from the end user after they have reached the end of their useful life. This paper deals with inventory control for a recycling system. For the system, we assume that demand is deterministic, and a fixed fraction of demands is returned and used as raw material of new products. We propose inventory policies and present procedures for determining the optimal policy parameters. Received: May 2005 / Accepted: December 2005     

A Deterministic Logical Semantics for Esterel

Esterel is a synchronous design language for the specification of reactive systems. There exist two main semantics for Esterel. On the one hand, the logical behavioral semantics provides a simple and compact formalization of the behavior of programs using SOS rules. But it does not ensure deterministic executions for all programs and all inputs. As non-deterministic programs have to be rejected as incorrect, this means it defines behaviors for incorrect programs, which is not convenient. On the other hand, the constructive semantics is deterministic (amongst other properties) but at the expense of a much more complex formalism. In this work, we construct and thoroughly analyze a new deterministic semantics for Esterel that retains the simplicity of the logical behavioral semantics, from which it derives. In our view, it provides a much better framework for formal reasoning about Esterel programs.     

Deterministic SkipNet

We present a deterministic scalable overlay network. In contrast, most previous overlay networks use randomness or hashing (pseudo-randomness) to achieve a uniform distribution of data and routing traffic.     

Multilinear formulas,maximal-partition discrepancy and mixed-sources extractors

We study a new method for proving lower bounds for subclasses of arithmetic circuits. Roughly speaking, the lower bound is proved by bounding the correlation between the coefficients' vector of a polynomial and the coefficients' vector of any product of two polynomials with disjoint sets of variables. We prove lower bounds for several old and new subclasses of circuits: monotone circuits, orthogonal formulas, non-canceling formulas, and noise-resistant formulas. One ingredient of our proof is an explicit map that has exponentially small discrepancy for every partition of the input variables into two sets of roughly the same size. We give two additional applications of this explicit map: to extractors construction and to communication complexity.     

确定性并行技术

由于执行个体之间的同步、竞争和干扰,并行程序的执行存在着不确定性问题,即程序在相同输入下多次执行可能得到不同的结果.不确定性给并行程序在开发、调试、测试、容错和安全等方面都带来了挑战,严重降低了并行程序的可靠性,阻碍了并行程序的发展.确定性并行技术通过控制并行程序执行个体间的同步、竞争和干扰,使程序的执行结果仅依赖于输入.确定性并行技术能够从根本上解决了目前并行程序存在的诸多问题,提升了并行程序的可靠性,给并行程序的发展带来了新的机遇.文中调查、分析和比较了目前主流的确定性并行技术和方法,分析了弱内存一致性对确定性并行系统的影响,并对未来确定性并行技术的发展趋势做出了展望.     

Affine extractors over large fields with exponential error

We describe a construction of explicit affine extractors over large finite fields with exponentially small error and linear output length. Our construction relies on a deep theorem of Deligne giving tight estimates for exponential sums over smooth varieties in high dimensions.     

Simple extractors via constructions of cryptographic pseudo-random generators

Trevisan has shown that constructions of pseudo-random generators from hard functions (the Nisan-Wigderson approach) also produce extractors. We show that constructions of pseudo-random generators from one-way permutations (the Blum-Micali-Yao approach) can be used for building extractors as well. Using this new technique we build extractors that do not use designs or polynomial-based error-correcting codes and that are very simple and efficient. For example, one extractor produces each output bit separately in O(log²n) time. These extractors work for weak sources with min-entropy λn, for arbitrary constant λ>0, have seed length O(log²n), and their output length is ≈n^λ/3.