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Articles 3901 - 3930 of 4258
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Verifying Completeness Of Relational Query Results In Data Publishing, Hwee Hwa Pang, Arpit Jain, Krithi Ramamritham, Kian-Lee Tan
Verifying Completeness Of Relational Query Results In Data Publishing, Hwee Hwa Pang, Arpit Jain, Krithi Ramamritham, Kian-Lee Tan
Research Collection School Of Computing and Information Systems
In data publishing, the owner delegates the role of satisfying user queries to a third-party publisher. As the publisher may be untrusted or susceptible to attacks, it could produce incorrect query results. In this paper, we introduce a scheme for users to verify that their query results are complete (i.e., no qualifying tuples are omitted) and authentic (i.e., all the result values originated from the owner). The scheme supports range selection on key and non-key attributes, project as well as join queries on relational databases. Moreover, the proposed scheme complies with access control policies, is computationally secure, and can be …
Conceptual Partitioning: An Efficient Method For Continuous Nearest Neighbor Monitoring, Kyriakos Mouratidis, Marios Hadjieleftheriou, Dimitris Papadias
Conceptual Partitioning: An Efficient Method For Continuous Nearest Neighbor Monitoring, Kyriakos Mouratidis, Marios Hadjieleftheriou, Dimitris Papadias
Research Collection School Of Computing and Information Systems
Given a set of objects P and a query point q, a k nearest neighbor (k-NN) query retrieves the k objects in P that lie closest to q. Even though the problem is well-studied for static datasets, the traditional methods do not extend to highly dynamic environments where multiple continuous queries require real-time results, and both objects and queries receive frequent location updates. In this paper we propose conceptual partitioning (CPM), a comprehensive technique for the efficient monitoring of continuous NN queries. CPM achieves low running time by handling location updates only from objects that fall in the vicinity of …
Breaking Public Key Cryptosystems On Tamper Resistant Devices In The Presence Of Transient Faults, Feng Bao, Robert H. Deng, Y. Han, A. Jeng, Arcot Desai Narasimhalu, T. Ngair
Breaking Public Key Cryptosystems On Tamper Resistant Devices In The Presence Of Transient Faults, Feng Bao, Robert H. Deng, Y. Han, A. Jeng, Arcot Desai Narasimhalu, T. Ngair
Research Collection School Of Computing and Information Systems
In this paper we present a method of attacking public-key cryptosystems (PKCs) on tamper resistant devices. The attack makes use of transient faults and seems applicable to many types of PKCs. In particular, we show how to attack the RSA, the E1Gamal signature scheme, the Schnorr signature scheme, and the DSA. We also present some possible methods to counter the attack.
Efficient Anonymous Roaming And Its Security Analysis, Guomin Yang, Duncan S. Wong, Xiaotie Deng
Efficient Anonymous Roaming And Its Security Analysis, Guomin Yang, Duncan S. Wong, Xiaotie Deng
Research Collection School Of Computing and Information Systems
The Canetti-Krawczyk (CK) model uses resuable modular components to construct indistinguishability-based key exchange protocols. The reusability of modular protocol components makes it easier to construct and prove new protocols when compared with other provably secure approaches. In this paper, we build an efficient anonymous and authenticated key exchange protocol for roaming by using the modular approach under the CK-model. Our protocol requires only four message flows and uses only standard cryptographic primitives. We also propose a one-pass counter based MT-authenticator and show its security under the assumption that there exists a MAC which is secure against chosen message attack.
A Semi-Supervised Active Learning Framework For Image Retrieval, Steven Hoi, Michael R. Lyu
A Semi-Supervised Active Learning Framework For Image Retrieval, Steven Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
Although recent studies have shown that unlabeled data are beneficial to boosting the image retrieval performance, very few approaches for image retrieval can learn with labeled and unlabeled data effectively. This paper proposes a novel semi-supervised active learning framework comprising a fusion of semi-supervised learning and support vector machines. We provide theoretical analysis of the active learning framework and present a simple yet effective active learning algorithm for image retrieval. Experiments are conducted on real-world color images to compare with traditional methods. The promising experimental results show that our proposed scheme significantly outperforms the previous approaches.
On Assigning Place Names To Geography Related Web Pages, Wenbo Zong, Dan Wu, Aixin Sun, Ee Peng Lim, Dion Hoe-Lian Goh
On Assigning Place Names To Geography Related Web Pages, Wenbo Zong, Dan Wu, Aixin Sun, Ee Peng Lim, Dion Hoe-Lian Goh
Research Collection School Of Computing and Information Systems
In this paper, we attempt to give spatial semantics to web pages by assigning them place names. The entire assignment task is divided into three sub-problems, namely place name extraction, place name disambiguation and place name assignment. We propose our approaches to address these sub-problems. In particular, we have modified GATE, a well-known named entity extraction software, to perform place name extraction using a US Census gazetteer. A rule-based place name disambiguation method and a place name assignment method capable of assigning place names to web page segments have also been proposed. We have evaluated our proposed disambiguation and assignment …
Dynamically-Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee-Hwa Pang
Dynamically-Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee-Hwa Pang
Research Collection School Of Computing and Information Systems
Traditional approaches to recommender systems have not taken into account situational information when making recommendations, and this seriously limits the relevance of the results. This paper advocates context-awareness as a promising approach to enhance the performance of recommenders, and introduces a mechanism to realize this approach. We present a framework that separates the contextual concerns from the actual recommendation module, so that contexts can be readily shared across applications. More importantly, we devise a learning algorithm to dynamically identify the optimal set of contexts for a specific recommendation task and user. An extensive series of experiments has validated that our …
Dynamically Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Dynamically Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Traditional approaches to recommender systems have not taken into account situational information when making recommendations, and this seriously limits the relevance of the results. This paper advocates context-awareness as a promising approach to enhance the performance of recommenders, and introduces a mechanism to realize this approach. We present a framework that separates the contextual concerns from the actual recommendation module, so that contexts can be readily shared across applications. More importantly, we devise a learning algorithm to dynamically identify the optimal set of contexts for a specific recommendation task and user. An extensive series of experiments has validated that our …
A New Architecture For User Authentication And Key Exchange Using Password For Federated Enterprises, Yanjiang Yang, Feng Bao, Robert H. Deng
A New Architecture For User Authentication And Key Exchange Using Password For Federated Enterprises, Yanjiang Yang, Feng Bao, Robert H. Deng
Research Collection School Of Computing and Information Systems
The rapid rise of federated enterprises entails a new way of trust management by the fact that an enterprise can account for partial trust of its affiliating organizations. On the other hand, password has historically been used as a main means for user authentication because of operational simplicity. We are thus motivated to explore the use of short password for user authentication and key exchange in the context of federated enterprises. Exploiting the special structure of a federated enterprise, our proposed new architecture comprises an external server managed by each affiliating organization and a central server managed by the enterprise …
Secure Human Communications Based On Biometrics Signals, Yongdong Wu, Feng Bao, Robert H. Deng
Secure Human Communications Based On Biometrics Signals, Yongdong Wu, Feng Bao, Robert H. Deng
Research Collection School Of Computing and Information Systems
User authentication is the first and probably the most challenging step in achieving secure person-to-person communications. Most of the existing authentication schemes require communicating parties either share a secret/password or know each other's public key. In this paper we suggest a novel user authentication scheme that is easy to use and overcomes the requirements of sharing password or public keys. Our scheme allows two human users to perform mutual authentication and have secure communications over an open channel by exchanging biometrics signals (e. g., voice or video signals). In addition to user authentication, our scheme establishes a secret session key …
Minimum Energy Reliable Paths Using Unreliable Wireless Links, Qunfeng Dong, Suman Banerjee, Micah Adler, Archan Misra
Minimum Energy Reliable Paths Using Unreliable Wireless Links, Qunfeng Dong, Suman Banerjee, Micah Adler, Archan Misra
Research Collection School Of Computing and Information Systems
We address the problem of energy-efficient reliable wireless communication in the presence of unreliable or lossy wireless link layers in multi-hop wireless networks. Prior work [1] has provided an optimal energy efficient solution to this problem for the case where link layers implement perfect reliability. However, a more common scenario --- a link layer that is not perfectly reliable, was left as an open problem. In this paper we first present two centralized algorithms, BAMER and GAMER, that optimally solve the minimum energy reliable communication problem in presence of unreliable links. Subsequently we present a distributed algorithm, DAMER, that approximates …
Leveraging Global Resources: A Distributed Process Maturity Framework For Software Product Development, Narayan Ramasubbu, M. S. Krishnan, Prasad Kompalli
Leveraging Global Resources: A Distributed Process Maturity Framework For Software Product Development, Narayan Ramasubbu, M. S. Krishnan, Prasad Kompalli
Research Collection School Of Computing and Information Systems
Distributed software development is pervasive in the software industry today as companies vie to leverage global resources. However, popular quality and process frameworks don?t specifically address the key processes needed for managing distributed software development. This practitioner-oriented, evolutionary process maturity framework for globally distributed software development features 24 new key process areas essential for managing distributed software product development and for continuously improving product management capabilities. An assessment survey helps practitioners implement the framework. In this article, the authors detail the framework and assessment survey, as well as report their experiences implementing the framework at a leading global firm. The …
Walverine: A Walrasian Trading Agent, Shih-Fen Cheng, Evan Leung, Kevin M. Lochner, Kevin O'Malley, Daniel M. Reeves, Julian L. Schvartzman, Michael P. Wellman
Walverine: A Walrasian Trading Agent, Shih-Fen Cheng, Evan Leung, Kevin M. Lochner, Kevin O'Malley, Daniel M. Reeves, Julian L. Schvartzman, Michael P. Wellman
Research Collection School Of Computing and Information Systems
TAC-02 was the third in a series of Trading Agent Competition events fostering research in automating trading strategies by showcasing alternate approaches in an open-invitation market game. TAC presents a challenging travel-shopping scenario where agents must satisfy client preferences for complementary and substitutable goods by interacting through a variety of market types. Michigan's entry, Walverine, bases its decisions on a competitive (Walrasian) analysis of the TAC travel economy. Using this Walrasian model, we construct a decision-theoretic formulation of the optimal bidding problem, which Walverine solves in each round of bidding for each good. Walverine's optimal bidding approach, as well as …
Providing Efficient Certification Services Against Active Attacks In Ad Hoc Networks, Bo Zhu, Guilin Wang, Zhiguo Wan, Mohan S. Kankanhalli, Feng Bao, Robert H. Deng
Providing Efficient Certification Services Against Active Attacks In Ad Hoc Networks, Bo Zhu, Guilin Wang, Zhiguo Wan, Mohan S. Kankanhalli, Feng Bao, Robert H. Deng
Research Collection School Of Computing and Information Systems
Most of previous research work in key management can only resist passive attacks, such as dropping the certificate request, and are vulnerable under active attacks, such as returning a fake reply to the node requesting the certification service. In this paper, we propose two algorithms to address both security and efficiency issues of certification services in ad hoc networks. Both of the algorithms can resist active attacks. In addition, simulation results show that, compared to the previous works, our second algorithm is not only much faster in a friendly environment, but it also works well in a hostile environment in …
Integrating User Feedback Log Into Relevance Feedback By Coupled Svm For Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu, Rong Jin
Integrating User Feedback Log Into Relevance Feedback By Coupled Svm For Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu, Rong Jin
Research Collection School Of Computing and Information Systems
Relevance feedback has been shown as an important tool to boost the retrieval performance in content-based image retrieval. In the past decade, various algorithms have been proposed to formulate relevance feedback in contentbased image retrieval. Traditional relevance feedback techniques mainly carry out the learning tasks by focusing lowlevel visual features of image content with little consideration on log information of user feedback. However, from a long-term learning perspective, the user feedback log is one of the most important resources to bridge the semantic gap problem in image retrieval. In this paper we propose a novel technique to integrate the log …
Predictive Neural Networks For Gene Expression Data Analysis, Ah-Hwee Tan, Hong Pan
Predictive Neural Networks For Gene Expression Data Analysis, Ah-Hwee Tan, Hong Pan
Research Collection School Of Computing and Information Systems
Gene expression data generated by DNA microarray experiments have provided a vast resource for medical diagnosis and disease understanding. Most prior work in analyzing gene expression data, however, focuses on predictive performance but not so much on deriving human understandable knowledge. This paper presents a systematic approach for learning and extracting rule-based knowledge from gene expression data. A class of predictive self-organizing networks known as Adaptive Resonance Associative Map (ARAM) is used for modelling gene expression data, whose learned knowledge can be transformed into a set of symbolic IF-THEN rules for interpretation. For dimensionality reduction, we illustrate how the system …
Effect Of Training Datasets On Support Vector Machine Prediction Of Protein-Protein Interactions, Siaw Ling Lo, Cong Zhong Cai, Maxey Chung, Yu Zong Chen
Effect Of Training Datasets On Support Vector Machine Prediction Of Protein-Protein Interactions, Siaw Ling Lo, Cong Zhong Cai, Maxey Chung, Yu Zong Chen
Research Collection School Of Computing and Information Systems
Knowledge of protein-protein interaction is useful for elucidating protein function via the concept of 'guilt-by-association'. A statistical learning method, Support Vector Machine (SVM), has recently been explored for the prediction of protein-protein interactions using artificial shuffled sequences as hypothetical noninteracting proteins and it has shown promising results (Bock, J. R., Gough, D. A., Bioinformatics 2001, 17, 455-460). It remains unclear however, how the prediction accuracy is affected if real protein sequences are used to represent noninteracting proteins. In this work, this effect is assessed by comparison of the results derived from the use of real protein sequences with that derived …
Video Text Detection And Segmentation For Optical Character Recognition, Chong-Wah Ngo, Chi-Kwong Chan
Video Text Detection And Segmentation For Optical Character Recognition, Chong-Wah Ngo, Chi-Kwong Chan
Research Collection School Of Computing and Information Systems
In this paper, we present approaches to detecting and segmenting text in videos. The proposed video-text-detection technique is capable of adaptively applying appropriate operators for video frames of different modalities by classifying the background complexities. Effective operators such as the repeated shifting operations are applied for the noise removal of images with high edge density. Meanwhile, a text-enhancement technique is used to highlight the text regions of low-contrast images. A coarse-to-fine projection technique is then employed to extract text lines from video frames. Experimental results indicate that the proposed text-detection approach is superior to the machine-learning-based (such as SVM and …
Fingerprinting Relational Databases: Schemes And Specialities, Yingjiu Li, Vipin Swarup, Sushil Jajodia
Fingerprinting Relational Databases: Schemes And Specialities, Yingjiu Li, Vipin Swarup, Sushil Jajodia
Research Collection School Of Computing and Information Systems
In this paper, we present a technique for fingerprinting relational data by extending Agrawal et al.'s watermarking scheme. The primary new capability provided by our scheme is that, under reasonable assumptions, it can embed and detect arbitrary bit-string marks in relations. This capability, which is not provided by prior techniques, permits our scheme to be used as a fingerprinting scheme. We then present quantitative models of the robustness properties of our scheme. These models demonstrate that fingerprints embedded by our scheme are detectable and robust against a wide variety of attacks including collusion attacks.
Evaluation Of Mpeg-4 Ipmp Extension, Hwee Hwa Pang, Yongdong Wu
Evaluation Of Mpeg-4 Ipmp Extension, Hwee Hwa Pang, Yongdong Wu
Research Collection School Of Computing and Information Systems
MPEG-4 IPMPX (intellectual property management and protection extension) is the latest ISO standard which provides a flexible framework for protecting MPEG streams. The message mechanism of IPMPX enables interoperability among IPMPX-compliant devices no matter which protection methods are embedded. This paper highlights several problems in the message syntax of IPMPX: the tool delivery message IPMP_ToolES_AU is vulnerable to network attack, the authentication message IMP_Mutual_Authentication is incapable of defending against forgery attack, and the configuration message IPMP_SelectiveDecrptionInit is ambiguous and redundant. We propose a number of remedies to those problems, which can be incorporated into a corrigenda to improve the present …
Mastaq: A Middleware Architecture For Sensor Applications With Statistical Quality Constraints, Inseok Hwang, Qi Han, Archan Misra
Mastaq: A Middleware Architecture For Sensor Applications With Statistical Quality Constraints, Inseok Hwang, Qi Han, Archan Misra
Research Collection School Of Computing and Information Systems
We present the design goals and functional components of MASTAQ, a data management middleware for pervasive applications that utilize sensor data. MASTAQ allows applications to specify their quality-of information (QoI) preferences (in terms of statistical metrics over the data) independent of the underlying network topology. It then achieves energy efficiency by adaptively activating and querying only the subset of sensor nodes needed to meet the target QoI bounds. We also present a closed-loop feedback mechanism based on broadcasting of activation probabilities, which allows MASTAQ to activate the appropriate number of sensors without requiring any inter-sensor coordination or knowledge of the …
The Value Of Mobile Applications: A Utility Company Study, Fiona Fui-Hoon Nah, Keng Siau, Hong Sheng
The Value Of Mobile Applications: A Utility Company Study, Fiona Fui-Hoon Nah, Keng Siau, Hong Sheng
Research Collection School Of Computing and Information Systems
The value proposition of mobile applications i.e. the net value of the benefits and costs associated with the adoption and adaptation of mobile applications is discussed. A means-ends network that depicts the fundamental relationships among the objectives such as efficiency, effectiveness, customer satisfaction, security, cost, and employee acceptance, was developed. The network is useful to researchers as it highlights the issues, concerns, and values of mobile applications. The network help the managers and practitioners to achieve their companies' objectives of implementing mobile and wireless applications.
Video Summarization And Scene Detection By Graph Modeling, Chong-Wah Ngo, Yu-Fei Ma, Hong-Jiang Zhang
Video Summarization And Scene Detection By Graph Modeling, Chong-Wah Ngo, Yu-Fei Ma, Hong-Jiang Zhang
Research Collection School Of Computing and Information Systems
In this paper, we propose a unified approach for video summarization based on the analysis of video structures and video highlights. Two major components in our approach are scene modeling and highlight detection. Scene modeling is achieved by normalized cut algorithm and temporal graph analysis, while highlight detection is accomplished by motion attention modeling. In our proposed approach, a video is represented as a complete undirected graph and the normalized cut algorithm is carried out to globally and optimally partition the graph into video clusters. The resulting clusters form a directed temporal graph and a shortest path algorithm is proposed …
Optimal Location Of Intermodal Freight Hubs, Illia Racunica, Laura Wynter
Optimal Location Of Intermodal Freight Hubs, Illia Racunica, Laura Wynter
Research Collection School Of Computing and Information Systems
We present an optimization model that has been developed to address the problem of increasing the share of rail in intermodal transport through the use of hub-and-spoke type networks for freight rail. The model defined is a generalization of the hub location problem in that it allows for non-linear and concave cost functions on different segments. A linearization procedure along with two efficient variable-reduction heuristics was developed for its resolution, making use of recent results on polyhedral properties of this class of problems. Computational experience and a qualitative analysis from a case study on the Alpine freight network is provided.
A Multi-Agent Approach For Solving Optimization Problems Involving Expensive Resources, Hoong Chuin Lau, H. Wang
A Multi-Agent Approach For Solving Optimization Problems Involving Expensive Resources, Hoong Chuin Lau, H. Wang
Research Collection School Of Computing and Information Systems
In this paper, we propose a multi-agent approach for solving a class of optimization problems involving expensive resources, where monolithic local search schemes perform miserably. More specifically, we study the class of bin-packing problems. Under our proposed Fine-Grained Agent System scheme, rational agents work both collaboratively and selfishly based on local search and mimic physics-motivated systems. We apply our approach to a generalization of bin-packing - the Inventory Routing Problem with Time Windows - which is an important logistics problem, and demonstrate the efficiency and effectiveness of our approach.
Robust Temporal Constraint Networks, Hoong Chuin Lau, Thomas Ou, Melvyn Sim
Robust Temporal Constraint Networks, Hoong Chuin Lau, Thomas Ou, Melvyn Sim
Research Collection School Of Computing and Information Systems
In this paper, we propose the Robust Temporal Constraint Network (RTCN) model for simple temporal constraint networks where activity durations are bounded by random variables. The problem is to determine whether such temporal network can be executed with failure probability less than a given 0 ≤ E ≤ 1 for each possible instantiation of the random variables, and if so. how one might find a feasible schedule with each given instantiation. The advantage of our model is that one can vary the value of ∊ to control the level of conservativeness of the solution. We present a computationally tractable and …
Linear Correlation Discovery In Databases: A Data Mining Approach, Cecil Chua, Roger Hsiang-Li Chiang, Ee Peng Lim
Linear Correlation Discovery In Databases: A Data Mining Approach, Cecil Chua, Roger Hsiang-Li Chiang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Very little research in knowledge discovery has studied how to incorporate statistical methods to automate linear correlation discovery (LCD). We present an automatic LCD methodology that adopts statistical measurement functions to discover correlations from databases’ attributes. Our methodology automatically pairs attribute groups having potential linear correlations, measures the linear correlation of each pair of attribute groups, and confirms the discovered correlation. The methodology is evaluated in two sets of experiments. The results demonstrate the methodology’s ability to facilitate linear correlation discovery for databases with a large amount of data.
The Effects Of Shilling On Final Bid Prices In Online Auctions, Robert J. Kauffman, Charles A. Wood
The Effects Of Shilling On Final Bid Prices In Online Auctions, Robert J. Kauffman, Charles A. Wood
Research Collection School Of Computing and Information Systems
An increasing number of reports of online auction fraud are of growing concern to auction operators and participants. In this research, we discuss reserve price shilling, where a bidder shills in order to avoid paying auction house fees, rather than to drive up the price of the final bid. We examine the effect that premium bids have upon the final selling price, since they are linked with reserve price shill bids. We use 10,260 eBay auctions during April 2001, and identify 919 auctions involving 322 sellers and 1583 bidders involved in concurrent auctions for the exact same item. We find …
Automatic Model Structuring From Text Using Biomedical Ontology, Joshi R., Li X., Ramachandaran S., Tze-Yun Leong
Automatic Model Structuring From Text Using Biomedical Ontology, Joshi R., Li X., Ramachandaran S., Tze-Yun Leong
Research Collection School Of Computing and Information Systems
Bayesian Networks and Influence Diagrams are effective methods for structuring clinical problems. Constructing a relevant structure without the numerical probabilities in itself is a challenging task. In addition, due to the rapid rate of innovations and new findings in the biomedical domain, constructing a relevant graphical model becomes even more challenging. Building a model structure from text with minimum intervention from domain experts and minimum training examples has always been a challenge for the researchers. In the biomedical domain, numerous advances have been made which may make this dream a possibility now. We are currently trying to build a general …
Method For Identifying Individuals, Manoj Thulasidas
Method For Identifying Individuals, Manoj Thulasidas
Research Collection School Of Computing and Information Systems
A method and system for identifying a subject comprises obtaining a digitised recording of an electrocardiogram measurement of the subject to be identified, the digitised recording being a cyclic waveform having a peak amplitude. The digitised recording is normalised to reduce variations due to physiological effects, and the normalised recording is processed to determine a feature vector in the frequency domain. The distance between the determined feature vector and a predetermined feature vector is measured to identify the subject.