Mechanising a formal model of flash memory

We present second steps in the construction of formal models of NAND flash memory, based on a recently emerged open standard for such devices. The model is intended as a key part of a pilot project to develop a verified file store system based on flash memory. The project was proposed by Joshi and Holzmann as a contribution to the Grand Challenge in Verified Software, and involves constructing a highly assured flash file store for use in space-flight missions. The model is at a level of abstraction that captures the internal architecture of NAND flash devices. In this paper, we focus on mechanising the state model and its initialisation operation, where most of the conceptual complexity resides.     

Identification of the Tennessee Eastman challenge process with subspace methods

The Tennessee Eastman challenge process is a realistic simulation of a chemical process that has been widely used in process control studies. In this case study, several identification methods are examined and used to develop MIMO models that contain seven inputs and ten outputs. ARX and finite impulse response models are identified using reduced-rank regression techniques (PLS and CCR) and state-space models identified with prediction error methods and subspace algorithms. For a variety of reasons, the only successful models are the state-space models produced by two popular subspace algorithms, N4SID and canonical variate analysis (CVA). The CVA model is the most accurate. Important issues for identifying the Tennessee Eastman challenge process and comparisons between the subspace algorithms are also discussed.     

《英国赛博安全战略：回顾与展望》评析

文章评估了英国赛博空间面临的机遇和威胁,对英国政府在赛博安全领域的投资进行了分析,揭示英国政府在赛博安全领域的最新进展和未来计划,针对英国政府可能面临的挑战提出了应对措施。     

基于SMS的移动电子商务安全问题与对策

文章首先介绍基于SMS的移动电子商务工作模式和安全需求,以此提出了移动电子商务系统的总体安全架构,然后分别从终端接入层、通信链路层、网关协议层、应用服务层四个层面分析了移动电子商务常见的安全问题,最后提出了以动态口令与"挑战"文本相结合的认证方式,以Hash算法实现签名,端到端的SMS移动电子商务安全技术方案。     

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 encryption, 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.     

Construction and analysis of ground models and their refinements as a foundation for validating computer-based systems

We explain why for the verified software challenge proposed in Hoare (J ACM 50(1): 63–69, 2003), Hoare and Misra (Verified software: theories, tools, experiments. Vision of a Grand Challenge project. In: [Meyer05]) to gain practical impact, one needs to include rigorous definitions and analysis, prior to code development and comprising both experimental validation and mathematical verification, of ground models, i.e., blueprints that describe the required application-content of programs. This implies the need to link via successive refinements the relevant properties of such high-level models in a traceable and checkable way to code a compiler can verify. We outline the Abstract State Machines (ASM) method, a discipline for reliable system development which allows one to bridge the gap between informal requirements and executable code by combining application-centric experimentally validatable system modelling with mathematically verifiable stepwise detailing of abstract models to compile-time-verifiable code.     

THE EFFICIENCY CHALLENGES OF RESOURCE DISCOVERY IN GRID ENVIRONMENTS

Resource discovery is one of the most important services that significantly affects the efficiency of grid computing systems. The inherent dynamic and large-scale characteristics of grid environments make their resource discovery a challenging task. In recent years, different approaches have been proposed for resource discovery, attempting to tackle the challenges of grid environments and improve the efficiency. Being aware of these challenges and approaches is worthwhile in order to choose an appropriate approach according to the application in different organizations. This study reviews the most important factors that should be considered and challenges to be tackled in order to develop an efficient grid resource discovery system.     

大数据教育应用前景分析及对策

近年来,以移动互联、云计算、数据挖掘等技术为基础的大数据技术迅猛发展,已逐渐应用到科技、信息化等各 个行业,成为驱动经济发展的重要引擎。随着教育信息化的不断深入,将新兴的大数据技术应用到教育领域已是大势所趋。 本文对大数据技术进行介绍,分析了大数据教育应用前景及风险挑战,提出可行的建议和措施,以促进大数据技术教育应用的 快速发展。     

Color space normalization: Enhancing the discriminating power of color spaces for face recognition

This paper presents the concept of color space normalization (CSN) and two CSN techniques, i.e., the within-color-component normalization technique (CSN-I) and the across-color-component normalization technique (CSN-II), for enhancing the discriminating power of color spaces for face recognition. Different color spaces usually display different discriminating power, and our experiments on a large scale face recognition grand challenge (FRGC) problem reveal that the RGB and XYZ color spaces are weaker than the I₁I₂I₃, YUV, YIQ, and LSLM color spaces for face recognition. We therefore apply our CSN techniques to normalize the weak color spaces, such as the RGB and the XYZ color spaces, the three hybrid color spaces XGB, YRB and ZRG, and 10 randomly generated color spaces. Experiments using the most challenging FRGC version 2 Experiment 4 with 12,776 training images, 16,028 controlled target images, and 8,014 uncontrolled query images, show that the proposed CSN techniques can significantly and consistently improve the discriminating power of the weak color spaces. Specifically, the normalized RGB, XYZ, XGB, and ZRG color spaces are more effective than or as effective as the I₁I₂I₃, YUV, YIQ and LSLM color spaces for face recognition. The additional experiments using the AR database validate the generalization of the proposed CSN techniques. We finally explain why the CSN techniques can improve the recognition performance of color spaces from the color component correlation point of view.     

外企在华经贸"逆动"行为与中国企业应对能力的提升

近年来，我国对外经济吸力不断增强，在华外企的作用愈来愈显重要。然而，随着全球化市场变化，外企在华出现了贸易垄断、相互结盟、资本转移、本土挖才和技术壁垒等“逆动’’行为。中国企业应通过提升国际直销经营力、外向渗透力、利用外资聚合力与知识产权创新力等核心竞争能力，实现外向经济更快发展。