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Research Collection School Of Computing and Information Systems

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Full-Text Articles in Physical Sciences and Mathematics

Efficient Client-To-Client Password Authenticated Key Exchange, Yanjiang Yang, Feng Bao, Robert H. Deng Dec 2008

Efficient Client-To-Client Password Authenticated Key Exchange, Yanjiang Yang, Feng Bao, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the rapid proliferation of client-to-client applications, PAKE (password authenticated key exchange) protocols in the client-to-client setting become increasingly important. In this paper, we propose an efficient client-to client PAKE protocol, which has much better performance than existing generic constructions. We also show that the proposed protocol is secure under a formal security model.

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Privacy Engine For Context-Aware Enterprise Application Services, Marion Blount, John Davis, Maria Ebling, William Jerome, Barry Leiba, Xuan Liu, Archan Misra Dec 2008

Privacy Engine For Context-Aware Enterprise Application Services, Marion Blount, John Davis, Maria Ebling, William Jerome, Barry Leiba, Xuan Liu, Archan Misra

Research Collection School Of Computing and Information Systems

Satisfying the varied privacy preferences of individuals, while exposing context data to authorized applications and individuals, remains a major challenge for context-aware computing. This paper describes our experiences in building a middleware component, the context privacy engine (CPE), that enforces a role-based, context-dependent privacy model for enterprise domains. While fundamentally an ACL-based access control scheme, CPE extends the traditional ACL mechanism with usage control and context constraints. This paper focuses on discussing issues related to managing and evaluating context-dependent privacy policies. Extensive experimental studies with a production-grade implementation and real-life context sources demonstrate that the CPE can support a large …

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Explaining Inferences In Bayesian Networks, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang Dec 2008

Explaining Inferences In Bayesian Networks, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

While Bayesian network (BN) can achieve accurate predictions even with erroneous or incomplete evidence, explaining the inferences remains a challenge. Existing approaches fall short because they do not exploit variable interactions and cannot account for compensations during inferences. This paper proposes the Explaining BN Inferences (EBI) procedure for explaining how variables interact to reach conclusions. EBI explains the value of a target node in terms of the influential nodes in the target's Markov blanket under specific contexts, where the Markov nodes include the target's parents, children, and the children's other parents. Working back from the target node, EBI shows the …

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Robust Regularized Kernel Regression, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu Dec 2008

Robust Regularized Kernel Regression, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual form, which is then solved by some quadratic program solver consequently. In this correspondence, we propose a new formulation for robust regularized kernel regression under the theoretical framework of regularization networks and then tackle the optimization problem directly in the primal. We show that the primal and dual approaches are equivalent to achieving similar regression performance, but the primal formulation is more efficient and easier to be implemented than the dual one. Different from …

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Scaling Up Multi-Agent Reinforcement Learning In Complex Domains, Dan Xiao, Ah-Hwee Tan Dec 2008

Scaling Up Multi-Agent Reinforcement Learning In Complex Domains, Dan Xiao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

TD-FALCON (Temporal Difference - Fusion Architecture for Learning, COgnition, and Navigation) is a class of self-organizing neural networks that incorporates Temporal Difference (TD) methods for real-time reinforcement learning. In this paper, we present two strategies, i.e. policy sharing and neighboring-agent mechanism, to further improve the learning efficiency of TD-FALCON in complex multi-agent domains. Through experiments on a traffic control problem domain and the herding task, we demonstrate that those strategies enable TD-FALCON to remain functional and adaptable in complex multi-agent domains

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Innovation In The Programmable Web: Characterizing The Mashup Ecosystem, C. Jason Woodard, Shuli Yu Dec 2008

Innovation In The Programmable Web: Characterizing The Mashup Ecosystem, C. Jason Woodard, Shuli Yu

Research Collection School Of Computing and Information Systems

This paper investigates the structure and dynamics of the Web 2.0 software ecosystem by analyzing empirical data on web service APIs and mashups. Using network analysis tools to visualize the growth of the ecosystem from December 2005 to 2007, we find that the APIs are organized into three tiers, and that mashups are often formed by combining APIs across tiers. Plotting the cumulative distribution of mashups to APIs reveals a power-law relationship, although the tail is short compared to previously reported distributions of book and movie sales. While this finding highlights the dominant role played by the most popular APIs …

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A Neural Network Model For A Hierarchical Spatio-Temporal Memory, Kiruthika Ramanathan, Luping Shi, Jianming Li, Kian Guan Lim, Zhi Ping Ang, Chong Chong Tow Nov 2008

A Neural Network Model For A Hierarchical Spatio-Temporal Memory, Kiruthika Ramanathan, Luping Shi, Jianming Li, Kian Guan Lim, Zhi Ping Ang, Chong Chong Tow

Research Collection School Of Computing and Information Systems

The architecture of the human cortex is uniform and hierarchical in nature. In this paper, we build upon works on hierarchical classification systems that model the cortex to develop a neural network representation for a hierarchical spatio-temporal memory (HST-M) system. The system implements spatial and temporal processing using neural network architectures. We have tested the algorithms developed against both the MLP and the Hierarchical Temporal Memory algorithms. Our results show definite improvement over MLP and are comparable to the performance of HTM.

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A New Framework For The Design And Analysis Of Identity-Based Identification Schemes, Guomin Yang, Jing Chen, Duncan S. Wong, Xiaotie Deng, Dongsheng Wang Nov 2008

A New Framework For The Design And Analysis Of Identity-Based Identification Schemes, Guomin Yang, Jing Chen, Duncan S. Wong, Xiaotie Deng, Dongsheng Wang

Research Collection School Of Computing and Information Systems

Constructing an identification scheme is one of the fundamental problems in cryptography, and is very useful in practice. An identity-based identification (IBI) scheme allows a prover to identify himself to a public verifier who knows only the claimed identity of the prover and some public information. In this paper, we propose a new framework for both the design and analysis of IBI schemes. Our approach works in an engineering way. We first identify an IBI scheme as the composition of two building blocks, and then show that, with different security properties of these building blocks, the corresponding IBI schemes can …

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Beyond Semantic Search: What You Observe May Not Be What You Think, Chong-Wah Ngo, Yu-Gang Jiang, Xiaoyong Wei, Wanlei Zhao, Feng Wang, Xiao Wu, Hung-Khoon Tan Nov 2008

Beyond Semantic Search: What You Observe May Not Be What You Think, Chong-Wah Ngo, Yu-Gang Jiang, Xiaoyong Wei, Wanlei Zhao, Feng Wang, Xiao Wu, Hung-Khoon Tan

Research Collection School Of Computing and Information Systems

This paper presents our approaches and results of the four TRECVID 2008 tasks we participated in: high-level feature extraction, automatic video search, video copy detection, and rushes summarization

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Market Liquidity Provision For On-Demand Computing, Zhiling Guo Nov 2008

Market Liquidity Provision For On-Demand Computing, Zhiling Guo

Research Collection School Of Computing and Information Systems

This paper focuses on a market intermediary’s role of liquidity provision to support on-demand computing in a dynamic market trading environment. We outline a framework in which a number of distributed agents sell and buy assets based on their changing utilities over time and a service provider acts as a market maker performing market intervention. We present benchmark models based on socially optimal liquidity provision and a brokerage framework. We then examine the benefits and the dealer’s incentives to provide market liquidity.

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Bias And Controversy In Evaluation Systems, Hady Wirawan Lauw, Ee Peng Lim, Ke Wang Nov 2008

Bias And Controversy In Evaluation Systems, Hady Wirawan Lauw, Ee Peng Lim, Ke Wang

Research Collection School Of Computing and Information Systems

Evaluation is prevalent in real life. With the advent of Web 2.0, online evaluation has become an important feature in many applications that involve information (e.g., video, photo, and audio) sharing and social networking (e.g., blogging). In these evaluation settings, a set of reviewers assign scores to a set of objects. As part of the evaluation analysis, we want to obtain fair reviews for all the given objects. However, the reality is that reviewers may deviate in their scores assigned to the same object, due to the potential bias of reviewers or controversy of objects. The statistical approach of averaging …

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Model-Driven Remote Attestation: Attesting Remote System From Behavioral Aspect, Liang Gu, Xuhua Ding, Robert H. Deng, Yanzhen Zou, Bing Xie, Weizhong Shao, Hong Mei Nov 2008

Model-Driven Remote Attestation: Attesting Remote System From Behavioral Aspect, Liang Gu, Xuhua Ding, Robert H. Deng, Yanzhen Zou, Bing Xie, Weizhong Shao, Hong Mei

Research Collection School Of Computing and Information Systems

Remote attestation was introduced in TCG specifications to determine whether a remote system is trusted to behave in a particular manner for a specific purpose; however, most of the existing approaches attest only the integrity state of a remote system and hence have a long way to go in achieving the above attestation objective. Behavior-based attestation and semantic attestation were recently introduced as solutions to approach the TCG attestation objective. In this paper, we extend behavior-based attestation to a model-driven remote attestation to prove that a remote system is trusted as defined by TCG. Our model-driven remote attestation verifies two …

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Modality Mixture Projections For Semantic Video Event Detection, Jialie Shen, Dacheng Tao, Xuelong Li Nov 2008

Modality Mixture Projections For Semantic Video Event Detection, Jialie Shen, Dacheng Tao, Xuelong Li

Research Collection School Of Computing and Information Systems

Event detection is one of the most fundamental components for various kinds of domain applications of video information system. In recent years, it has gained a considerable interest of practitioners and academics from different areas. While detecting video event has been the subject of extensive research efforts recently, much less existing approach has considered multimodal information and related efficiency issues. In this paper, we use a subspace selection technique to achieve fast and accurate video event detection using a subspace selection technique. The approach is capable of discriminating different classes and preserving the intramodal geometry of samples within an identical …

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Two-Factor Mutual Authentication Based On Smart Cards And Passwords, Guomin Yang, Duncan S. Wong, Huaxiong Wang, Xiaotie Deng Nov 2008

Two-Factor Mutual Authentication Based On Smart Cards And Passwords, Guomin Yang, Duncan S. Wong, Huaxiong Wang, Xiaotie Deng

Research Collection School Of Computing and Information Systems

One of the most commonly used two-factor user authentication mechanisms nowadays is based on smart-card and password. A scheme of this type is called a smart-card-based password authentication scheme. The core feature of such a scheme is to enforce two-factor authentication in the sense that the client must have the smart-card and know the password in order to gain access to the server. In this paper, we scrutinize the security requirements of this kind of schemes, and propose a new scheme and a generic construction framework for smart-card-based password authentication. We show that a secure password based key exchange protocol …

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Profile-Guided Program Simplification For Effective Testing And Analysis, Lingxiao Jiang, Zhendong Su Nov 2008

Profile-Guided Program Simplification For Effective Testing And Analysis, Lingxiao Jiang, Zhendong Su

Research Collection School Of Computing and Information Systems

Many testing and analysis techniques have been developed for inhouse use. Although they are effective at discovering defects before a program is deployed, these techniques are often limited due to the complexity of real-world code and thus miss program faults. It will be the users of the program who eventually experience failures caused by the undetected faults. To take advantage of the large number of program runs carried by the users, recent work has proposed techniques to collect execution profiles from the users for developers to perform post-deployment failure analysis. However, in order to protect users' privacy and to reduce …

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Selection Of Concept Detectors For Video Search By Ontology-Enriched Semantic Spaces, Xiao-Yong Wei, Chong-Wah Ngo, Yu-Gang Jiang Oct 2008

Selection Of Concept Detectors For Video Search By Ontology-Enriched Semantic Spaces, Xiao-Yong Wei, Chong-Wah Ngo, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

This paper describes the construction and utilization of two novel semantic spaces, namely Ontology-enriched Semantic Space (OSS) and Ontology-enriched Orthogonal Semantic Space (OS2), to facilitate the selection of concept detectors for video search. These two semantic spaces are enriched with ontology knowledge, while emphasizing consistent and uniform comparison of ontological relatedness among concepts for query-to-concept mapping. OS2, in addition to being a linear space like OSS, also guarantees orthogonality of the semantic space. Compared with other ontology reasoning measures, both spaces are capable of providing platforms that offer a global view of concept inter-relatedness, by allowing evaluation of concept similarity …

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Impacts Of Information And Communication Technologies On Country Development: Accounting For Area Interrelationships, Robert J. Kauffman, Ajay Kumar Oct 2008

Impacts Of Information And Communication Technologies On Country Development: Accounting For Area Interrelationships, Robert J. Kauffman, Ajay Kumar

Research Collection School Of Computing and Information Systems

Single-item composite indices gauge ICT readiness at the country level but do not represent the direct impact of ICTs on a country's development. This paper describes a new approach to measuring the macrolevel impacts of ICTs across a range of development areas. The indirect effects of one area on others is taken into consideration by a simultaneous equation model that permits the inclusion of multiple development areas. The model is applied to data pertaining to four development areas in 64 countries: trade flows, agricultural productivity, R&D, and quality of life. ICT readiness is found to have a positive association with …

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Ontology Enhanced Web Image Retrieval: Aided By Wikipedia And Spreading Activation Theory, Huan Wang, Xing Jiang, Liang-Tien Chia, Ah-Hwee Tan Oct 2008

Ontology Enhanced Web Image Retrieval: Aided By Wikipedia And Spreading Activation Theory, Huan Wang, Xing Jiang, Liang-Tien Chia, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Ontology, as an efective approach to bridge the semantic gap in various domains, has attracted a lot of interests from multimedia researchers. Among the numerous possibilities enabled by ontology, we are particularly interested in exploiting ontology for a better understanding of media task (particularly, images) on the World Wide Web. To achieve our goal, two open issues are inevitably involved: 1) How to avoid the tedious manual work for ontology construction? 2) What are the effective inference models when using an ontology? Recent works about ontology learned from Wikipedia has been reported in conferences targeting the areas of knowledge management …

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Ontology-Based Visual Word Matching For Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo Oct 2008

Ontology-Based Visual Word Matching For Near-Duplicate Retrieval, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper proposes a novel approach to exploit the ontological relationship of visual words by linguistic reasoning. A visual word ontology is constructed to facilitate the rigorous evaluation of linguistic similarity across visual words. The linguistic similarity measurement enables cross-bin matching of visual words, compromising the effectiveness and speed of conventional keypoint matching and bag-of-word approaches. A constraint EMD is proposed and experimented to efficiently match visual words. Empirical findings indicate that the proposed approach offers satisfactory performance to near-duplicate retrieval, while still enjoying the merit of speed efficiency compared with other techniques.

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Modeling Video Hyperlinks With Hypergraph For Web Video Reranking, Hung-Khoon Tan, Chong-Wah Ngo, Xiao Wu Oct 2008

Modeling Video Hyperlinks With Hypergraph For Web Video Reranking, Hung-Khoon Tan, Chong-Wah Ngo, Xiao Wu

Research Collection School Of Computing and Information Systems

In this paper, we investigate a novel approach of exploiting visual-duplicates for web video reranking using hypergraph. Current graph-based reranking approaches consider mainly the pair-wise linking of keyframes and ignore reliability issues that are inherent in such representation. We exploit higher order relation to overcome the issues of missing links in visual-duplicate keyframes and in addition identify the latent relationships among keyframes. Based on hypergraph, we consider two groups of video threads: visual near-duplicate threads and story threads, to hyperlink web videos and describe the higher order information existing in video content. To facilitate reranking using random walk algorithm, the …

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Video Event Detection Using Motion Relativity And Visual Relatedness, Feng Wang, Yu-Gang Jiang, Chong-Wah Ngo Oct 2008

Video Event Detection Using Motion Relativity And Visual Relatedness, Feng Wang, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Event detection plays an essential role in video content analysis. However, the existing features are still weak in event detection because: i) most features just capture what is involved in an event or how the event evolves separately, and thus cannot completely describe the event; ii) to capture event evolution information, only motion distribution over the whole frame is used which proves to be noisy in unconstrained videos; iii) the estimated object motion is usually distorted by camera movement. To cope with these problems, in this paper, we propose a new motion feature, namely Expanded Relative Motion Histogram of Bag-ofVisual-Words …

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Determining The Number Of Bp Neural Network Hidden Layer Units, Huayu Shen, Zhaoxia Wang, Chengyao Gao, Juan Qin, Fubin Yao, Wei Xu Oct 2008

Determining The Number Of Bp Neural Network Hidden Layer Units, Huayu Shen, Zhaoxia Wang, Chengyao Gao, Juan Qin, Fubin Yao, Wei Xu

Research Collection School Of Computing and Information Systems

This paper proposed an improved method to contrapose the problem which is difficult to determine the number of BP neural network hidden layer units. it is proved that the method is efficeient in reducing the frequency of the test through experients, and improves the efficiency of determining the best number of hidden units, which is more valuable in the applications.

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Understanding Evolution In Technology Ecosystems, Gediminas Adomavicius, Jesse Bockstedt, Alok Gupta, Robert J. Kauffman Oct 2008

Understanding Evolution In Technology Ecosystems, Gediminas Adomavicius, Jesse Bockstedt, Alok Gupta, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

The current environment of information technology can be a complex place for analysts and firms to navigate, especially when making decisions about new product development, technology investment, and technology planning. Many industry analysts recognize that it is difficult, if not impossible, to accurately predict future technological advances. However, successful firms need to understand the nature of technological change and evolution in order to accurately forecast and take advantage of investment and market opportunities. For example, although RFID has been in the news for the past decade as the potential distribution and retail "killer technology", uncertainties about its future technical capabilities, …

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Output Regularized Metric Learning With Side Information, Wei Liu, Steven C. H. Hoi, Jianzhuang Liu Oct 2008

Output Regularized Metric Learning With Side Information, Wei Liu, Steven C. H. Hoi, Jianzhuang Liu

Research Collection School Of Computing and Information Systems

Distance metric learning has been widely investigated in machine learning and information retrieval. In this paper, we study a particular content-based image retrieval application of learning distance metrics from historical relevance feedback log data, which leads to a novel scenario called collaborative image retrieval. The log data provide the side information expressed as relevance judgements between image pairs. Exploiting the side information as well as inherent neighborhood structures among examples, we design a convex regularizer upon which a novel distance metric learning approach, named output regularized metric learning, is presented to tackle collaborative image retrieval. Different from previous distance metric …

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Representative Entry Selection For Profiling Blogs, Jinfeng Zhuang, Steven C. H. Hoi, Aixin Sun, Rong Jin Oct 2008

Representative Entry Selection For Profiling Blogs, Jinfeng Zhuang, Steven C. H. Hoi, Aixin Sun, Rong Jin

Research Collection School Of Computing and Information Systems

Many applications on blog search and mining often meet the challenge of handling huge volume of blog data, in which one single blog could contain hundreds or even thousands of entries. We investigate novel techniques for profiling blogs by selecting a subset of representative entries for each blog. We propose two principles for guiding the entry selection task: representativeness and diversity. Further, we formulate the entry selection task into a combinatorial optimization problem and propose a greedy yet effective algorithm for finding a good approximate solution by exploiting the theory of submodular functions. We suggest blog classification for judging the …

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A Study Of Early Stage Game Design And Prototyping, Brien Colwell, Richard C. Davis, James A. Landay Oct 2008

A Study Of Early Stage Game Design And Prototyping, Brien Colwell, Richard C. Davis, James A. Landay

Research Collection School Of Computing and Information Systems

Computer games and simulations can be valuable teaching and communication tools, and they are a powerful form of self-expression. Unfortunately, creating games requires programming, and programming requires time and skill. Some tools facilitate game creation to motivate novice programmers, but programming is still necessary. Other systems require less programming, but they are narrowly focused. To enable faster, simpler, and more expressive tools for professionals and amateurs, we have explored the processes and tools used in the early stages of game and simulation design. Interviews with educators clarified the uses of simulations in the classroom, while interviews with professional game designers …

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Specifying And Verifying Event-Based Fairness Enhanced Systems, Jun Sun, Yang Liu, Jin Song Dong, Hai H. Wang Oct 2008

Specifying And Verifying Event-Based Fairness Enhanced Systems, Jun Sun, Yang Liu, Jin Song Dong, Hai H. Wang

Research Collection School Of Computing and Information Systems

Liveness/Fairness plays an important role in software specification, verification and development. Existing event-based compositional models are safety-centric. In this paper, we describe a framework for systematically specifying and verifying event-based systems under fairness assumptions. We introduce different event annotations to associate fairness constraints with individual events. Fairness annotated events can be used to embed liveness/fairness assumptions in event-based models flexibly and naturally. We show that state-of-the-art verification algorithms can be extended to verify models under fairness assumptions, with little computational overhead. We further improve the algorithm by other model checking techniques like partial order reduction. A toolset named Pat has …

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Model Checking Csp Revisited: Introducing A Process Analysis Toolkit, Jun Sun, Yang Liu, Jin Song Dong Oct 2008

Model Checking Csp Revisited: Introducing A Process Analysis Toolkit, Jun Sun, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

FDR, initially introduced decades ago, is the de facto analyzer for Communicating Sequential Processes (CSP). Model checking techniques have been evolved rapidly since then. This paper describes PAT, i.e., a process analysis toolkit which complements FDR in several aspects. PAT is designed to analyze event-based compositional system models specified using CSP as well as shared variables and asynchronous message passing. It supports automated refinement checking, model checking of LTL extended with events, etc. In this paper, we highlight how partial order reduction is applied to improve refinement checking in PAT. Experiment results show that PAT outperforms FDR in some cases.

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Specification Mining Of Symbolic Scenario-Based Models, David Lo, Shahar Maoz Oct 2008

Specification Mining Of Symbolic Scenario-Based Models, David Lo, Shahar Maoz

Research Collection School Of Computing and Information Systems

Many dynamic analysis approaches to specification mining, which extract behavioral models from execution traces, do not consider object identities. This limits their power when used to analyze traces of general object oriented programs. In this work we present a novel specification mining approach that considers object identities, and, moreover, generalizes from specifications involving concrete objects to their symbolic class-level abstractions. Our approach uses data mining methods to extract significant scenario-based specifications in the form of Damm and Harel's live sequence charts (LSC), a formal and expressive extension of classic sequence diagrams. We guarantee that all mined symbolic LSCs are significant …

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Remote Attestation On Program Execution, Liang Gu, Xuhua Ding, Robert H. Deng, Bing Xie, Hong Mei Oct 2008

Remote Attestation On Program Execution, Liang Gu, Xuhua Ding, Robert H. Deng, Bing Xie, Hong Mei

Research Collection School Of Computing and Information Systems

Remote attestation provides the basis for one platform to establish trusts on another. In this paper, we consider the problem of attesting the correctness of program executions. We propose to measure the target program and all the objects it depends on, with an assumption that the Secure Kernel and the Trusted Platform Module provide a secure execution environment through process separation. The attestation of the target program begins with a program analysis on the source code or the binary code in order to find out the relevant executables and data objects. Whenever such a data object is accessed or a …

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