An LMI approach to minimum sensitivity analysis with application to fault detection

This paper systematically studies the minimum input sensitivity analysis problem. The lowest level of sensitivity of system outputs to system inputs is defined as an H_- index. A full characterization of the H_- index is given, first, in terms of matrix equalities and inequalities, and then in terms of linear matrix inequalities (LMIs), as a dual of the Bounded Real Lemma. A related problem of input observability is also studied, with new necessary and sufficient conditions given, which are necessary for a fault detection system to have a nonzero worst-case fault sensitivity. The above results are applied to the problem of fault detection filter analysis, with numerical examples given to show the effectiveness of the proposed approaches.     

基于粗糙熵的离群点检测方法及其在无监督入侵检测中的应用

香农的信息熵被广泛用于粗糙集.利用粗糙集中的粗糙熵来检测离群点,提出一种基于粗糙熵的离群点检测方法,并应用于无监督入侵检测.首先,基于粗糙熵提出一种新的离群点定义,并设计出相应的离群点检测算法-–基于粗糙熵的离群点检测(rough entropy-based outlier detection,REOD);其次,通过将入侵行为看作是离群点,将REOD应用于入侵检测中,从而得到一种新的无监督入侵检测方法.通过多个数据集上的实验表明,REOD具有良好的离群点检测性能.另外,相对于现有的入侵检测方法,REOD具有较高的入侵检测率和较低的误报率,特别是其计算开销较小,适合于在海量高维的数据中检测入侵.     

基于多层次多角度分析的网络安全态势感知

精确描述网络系统的安全态势是当前网络安全研究的热点,目前对网络系统安全性的理解和预测,大多进行的是定性方面的分析,并且由于出发点、目的等的不同,很难得到一个让各方都满意的结果。本文在准确感知网络系统安全性相关数据的基础上,提出包括网络安全态势专题评估、要素评估和整体评估的多层次多角度评估模型来对网络系统安全性进行评估,保证了评估结果准确、客观和全面。     

An ontology-based approach to security pattern selection

Usually, the security requirements are addressed by abstracting the security problems arising in a specific context and providing a well proven solution to them. Security patterns incorporating proven security expertise solution to the recurring security problems have been widely accepted by the community of security engineering. The fundamental challenge for using security patterns to satisfy security requirements is the lack of defined syntax, which makes it impossible to ask meaningful questions and get semantically meaningful answers. Therefore, this paper presents an ontological approach to facilitating security knowledge mapping from security requirements to their corresponding solutions–security patterns. Ontologies have been developed usingWeb Ontology Language (OWL) and then incorporated into a security pattern search engine which enables sophisticated search and retrieval of security patterns using the proposed algorithm. Applying the introduced approach allows security novices to reuse security expertise to develop secure software system.     

An approach for modeling and analysis of security system architectures

Security system architecture governs the composition of components in security systems and interactions between them. It plays a central role in the design of software security systems that ensure secure access to distributed resources in networked environment. In particular, the composition of the systems must consistently assure security policies that it is supposed to enforce. However, there is currently no rigorous and systematic way to predict and assure such critical properties in security system design. A systematic approach is introduced to address the problem. We present a methodology for modeling security system architecture and for verifying whether required security constraints are assured by the composition of the components. We introduce the concept of security constraint patterns, which formally specify the generic form of security policies that all implementations of the system architecture must enforce. The analysis of the architecture is driven by the propagation of the global security constraints onto the components in an incremental process. We show that our methodology is both flexible and scalable. It is argued that such a methodology not only ensures the integrity of critical early design decisions, but also provides a framework to guide correct implementations of the design. We demonstrate the methodology through a case study in which we model and analyze the architecture of the Resource Access Decision (RAD) Facility, an OMG standard for application-level authorization service.     

An approach to discovering multi-temporal patterns and its application to financial databases

Managerial decision-making processes often involve data of the time nature and need to understand complex temporal associations among events. Extending classical association rule mining approaches in consideration of time in order to obtain temporal information/knowledge is deemed important for decision support, which is nowadays one of the key issues in business intelligence. This paper presents the notion of multi-temporal patterns with four different temporal predicates, namely before, during, equal and overlap, and discusses a number of related properties, based on which a mining algorithm is designed. This enables us to effectively discover multi-temporal patterns in large-scale temporal databases by reducing the database scan in the generation of candidate patterns. The proposed approach is then applied to stock markets, aimed at exploring possible associative movements between the stock markets of Chinese mainland and Hong Kong so as to provide helpful knowledge for investment decisions.     

克隆代码分析方法研究

针对已有克隆代码检测工具只输出克隆组形式的检测结果,而无法分析克隆代码对软件质量的影响问题,提出危害软件质量的关键克隆代码的识别方法。首先,定义了克隆代码的统一表示形式,使之可以分析各种克隆检测工具的检测结果;接下来,解析源程序和克隆检测结果,识别标识符命名不一致性潜在缺陷;然后,定义了克隆关联图,在此基础上检测跨越多个实现不同功能的文件、危害软件可维护性的克隆代码;最后,对检测结果进行可视化统计分析。本文的克隆代码分析工具被应用于分析开源代码httpd,检测出了1组标识符命名不一致的克隆代码和44组危害软件可维护性的关键克隆类,实验结果表明,本文方法可以有效辅助软件开发和维护人员分析、维护克隆代码。     

A rule dynamics approach to event detection in Twitter with its application to sports and politics

The increasing popularity of Twitter as social network tool for opinion expression as well as information retrieval has resulted in the need to derive computational means to detect and track relevant topics/events in the network. The application of topic detection and tracking methods to tweets enable users to extract newsworthy content from the vast and somehow chaotic Twitter stream. In this paper, we apply our technique named Transaction-based Rule Change Mining to extract newsworthy hashtag keywords present in tweets from two different domains namely; sports (The English FA Cup 2012) and politics (US Presidential Elections 2012 and Super Tuesday 2012). Noting the peculiar nature of event dynamics in these two domains, we apply different time-windows and update rates to each of the datasets in order to study their impact on performance. The performance effectiveness results reveal that our approach is able to accurately detect and track newsworthy content. In addition, the results show that the adaptation of the time-window exhibits better performance especially on the sports dataset, which can be attributed to the usually shorter duration of football events.     

An approach for visual attention based on biquaternion and its application for ship detection in multispectral imagery

This paper proposes an approach for visual attention based on biquaternion, and investigates its application for ship detection in multispectral imagery. The proposed approach describes high-dimensional data in the form of biquaternion and utilizes the phase spectrum of biquaternion Fourier transform to generate a required saliency map that can be used for salient target detection. In our method, the multidimensional data is processed as a whole, and the features contained in each spectral band can be extracted effectively. Compared with traditional visual attention approaches, our method has very low computational complexity. Experimental results on simulated and real multispectral remote sensing data have shown that the proposed method has excellent performance in ship detection. Furthermore, our method is robust against white noise and almost meets real-time requirements, which has great potentials in engineering applications.     

An integrated approach to selective-disassembly sequence planning

De-manufacturing (DM) is defined as a process to disassemble certain parts or components from a product. The parts or components are selected for recycling, reuse, maintenance or disposal. Selective-disassembly as the disassembly of the selected parts is a key process in DM. Allowing a partial and non-procedural disassembly sequence in DM, selective-disassembly aims to minimize the number of removals regardless of assembly indenture levels. It is necessary for selective-disassembly to have an effective and optimal sequence planning in order to reduce tremendous time and cost involved in product DM. The Wave propagation (WP) method, a dominant approach to selective-disassembly sequence planning, focuses on topological disassemblability of parts. It is inefficient to achieve the aim because of two missed considerations: tool accessibility to a fastener in non-procedural and partial disassembly, and batch removability to directly access a part for separation or replacement.This paper presents an integrated approach to selective-disassembly sequence planning. The two examples presented here demonstrate that the approach is efficient and practical for DM. The implemented approach can efficiently generate a feasible and near-optimal sequence plan for selective-disassembly, with ensuring both batch disassembly of components and tool accessibility to fasteners.     

XRound: A reversible template language and its application in model-based security analysis

Successful analysis of the models used in Model-Driven Development requires the ability to synthesise the results of analysis and automatically integrate these results with the models themselves. This paper presents a reversible template language called XRound which supports round-trip transformations between models and the logic used to encode system properties. A template processor that supports the language is described, and the use of the template language is illustrated by its application in an analysis workbench, designed to support analysis of security properties of UML and MOF-based models. As a result of using reversible templates, it is possible to seamlessly and automatically integrate the results of a security analysis with a model.     

基于系统调用序列分析的入侵检测方法

提出了一种改进的基于系统调用序列分析的入侵检测方法,该方法对审计数据首先进行MLSI现象的检测,在发现MLSI之后,再与正常库进行匹配,以检测是否有入侵行为.理论分析和实验表明,MLSI能够有效地标识入侵,通过查找MLSI,再进行异常检测的方法可以大大地降低系统的开销,这些都说明该方法是有效和可行的.     

An approach to decision-making with triangular fuzzy reciprocal preference relations and its application

Triangular fuzzy reciprocal preference relations (TFRPRs) are powerful tools to denoting decision-makers’ fuzzy judgments, which permit the decision-makers to apply triangular fuzzy ratio rather than real numbers to express their judgements. Consistency analysis is one of the most crucial issues in preference relations that can guarantee the reasonable ranking order. However, all previous consistency concepts cannot well address this type of preference relations. Based on the operational laws on triangular fuzzy numbers, this paper introduces an additive consistency concept for TFRPRs by using quasi TFRPRs, which can be seen as a natural extension of the crisp case. Using this consistency concept, models to judging the additive consistency of TFRPRs and to estimating missing values in complete TFRPRs are constructed. Then, an algorithm to decision-making with TFRPRs is developed. Finally, two numerical examples are offered to illustrate the application of the proposed procedure, and comparison analysis is performed.     

An efficient face detection based on color-filtering and its application to smart devices

This paper proposes a means of using facial color to enhance conventional face detectors. To detect face rapidly, the proposed approach adopts a color filtering based efficient region scanning method. The scanning method skips over regions that do not contain candidate faces, based on a facial color membership function. Then it adopts a face/non-face classifier using facial color at the preprocessor of the face detector. This classifier has low computational cost and can reject non-face regions at an early stage of face detection. By integrating the proposed face detector with a kernel based object tracker, a real-time face detection and tracking application is implemented for smart devices. The proposed method considerably reduces the overall computation time and reduces the number of false alarms.     

A convex optimization approach for clone detection in wireless sensor networks

When deployed unattended in hostile environments, static and mobile Wireless Sensor Networks (WSNs) are vulnerable to node capture and cloning attacks, where an adversary physically compromises network nodes and extracts all information known to them, including the assigned cryptographic material and the internal states of network protocols. The obtained knowledge is used to disrupt the network by deploying and controlling copies of captured nodes (clones). Recently, a variety of novel clone detection methods have been developed, using concepts such as birthday paradox, sequential detection or random encounters in mobile environments. At present there is no framework to evaluate an individual detection method based on the WSN performance under attack or to compare and choose a method appropriate for a given application. In this paper, we develop an optimization framework for choosing the parameters of a detection method so that the cost of clone detection is minimized. We show that every detection method can be characterized in terms of four costs, namely, the impact of leaving undetected cloned nodes in the network, the cost of revoking nodes falsely identified as compromised, and the costs of communication and storage. A convex combination of these costs defines the cost of clone detection, which is then minimized with respect to the parameters of the detection method. Using this framework, we analyze existing clone detection algorithms and provide efficient methods for obtaining optimal detection parameters.     

量子点生物传感器及其在生物医学分析检测中的应用

综述了基于新型半导体纳米材料—量子点(QDs)的各种生物传感器如荧光生物传感器、微流控芯片生物传感器、光纤生物传感器、适配体生物传感器、分子马达生物传感器等的原理、特点,并对其在生物医学分析检测中的应用与其发展的局限性与发展前景进行了综述.     

An object-oriented approach to application generation

The TUBA system consists of a set of integrated tools for the generation of business-oriented applications. Tools and applications have a modular structure, represented by class objects. The article describes the architecture of the environments for file processing, screen handling and report writing.     

Uncorrelated minimum-length sequence and its application to parameter estimation

This paper deals with a realization of an input sequence for estimating the response function of a discrete linear system with noisy observations. It is shown that the input sequence can be given by the repetition of the uncorrelated minimum-length sequences whose amplitude takes the maximum values under a given amplitude-constraint. The realization of the sequences is treated as a block design problem in combinatorial analysis. As a result, the sequences are characterized by an extended form of block design. Thus the input sequences may be obtained and are denoted the UM (uncorrelated minimum-length) sequences for abbreviation.