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Full-Text Articles in Entire DC Network
A New Framework For Rfid Privacy, Robert H. Deng, Yingjiu Li, Moti Yung, Yunlei Zhao
A New Framework For Rfid Privacy, Robert H. Deng, Yingjiu Li, Moti Yung, Yunlei Zhao
Research Collection School Of Computing and Information Systems
Formal RFID security and privacy frameworks are fundamental to the design and analysis of robust RFID systems. In this paper, we develop a new definitional framework for RFID privacy in a rigorous and precise manner. Our framework is based on a zero-knowledge (ZK) formulation [8,6] and incorporates the notions of adaptive completeness and mutual authentication. We provide meticulous justification of the new framework and contrast it with existing ones in the literature. In particular, we prove that our framework is strictly stronger than the ind-privacy model of [18], which answers an open question posed in [18] for developing stronger RFID …
Do Online Reviews Reflect A Product’S True Perceived Quality? An Investigation Of Online Movie Reviews Across Cultures, Noi Sian Koh, Nan Hu, Eric K. Clemons
Do Online Reviews Reflect A Product’S True Perceived Quality? An Investigation Of Online Movie Reviews Across Cultures, Noi Sian Koh, Nan Hu, Eric K. Clemons
Research Collection School Of Computing and Information Systems
This paper investigates when the reported average of online ratings matches the perceived average assessment of the population as a whole, including the average assessments of both raters and non-raters. We apply behavioral theory to capture intentions in rating online movie reviews in two dissimilar countries – China and the United States. We argue that consumers’ rating behaviors are affected by cultural influences and that they are influenced in predictable ways. Based on data collected from IMDB.com and Douban.com, we found significant differences across raters from these two different cultures. Additionally, we examined how cultural elements influence rating behavior for …
Pseudonym-Based Rfid Discovery Service To Mitigate Unauthorized Tracking In Supply Chain Management, Qiang Yan, Robert H. Deng, Zheng Yan, Yingjiu Li, Tieyan Li
Pseudonym-Based Rfid Discovery Service To Mitigate Unauthorized Tracking In Supply Chain Management, Qiang Yan, Robert H. Deng, Zheng Yan, Yingjiu Li, Tieyan Li
Research Collection School Of Computing and Information Systems
Unauthorized tracking of RFID tagged assets at the system level, where an adversary tracks movement of RFID tagged assets by eavesdropping network messages or compromising date center servers, has not been well recognized in prior research. Compared to the traditional unauthorized tracking by clandestine scanning at the physical level, unauthorized tracking at the system level could be even more harmful as the adversary is able to obtain tracking information on a global scale and without physical presence. This paper analyzes the threat of unauthorized tracking by a semi-trusted RFID Discovery Service which maintains a database of RFID tag location records …
Event Study Method For Validating Agent-Based Trading Simulations, Shih-Fen Cheng
Event Study Method For Validating Agent-Based Trading Simulations, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
In this paper, we introduce how one can validate an event-centric trading simulation platform that is built with multi-agent technology. The issue of validation is extremely important for agent-based simulations, but unfortunately, so far there is no one universal method that would work in all domains. The primary contribution of this paper is a novel combination of event-centric simulation design and event study approach for market dynamics generation and validation. In our event-centric design, the simulation is progressed by announcing news events that affect market prices. Upon receiving these events, event-aware software agents would adjust their views on the market …
P2pdoctagger: Content Management Through Automated P2p Collaborative Tagging, Hock Hee Ang, Vivekanand Gopalkrishnan, Wee Keong Ng, Steven C. H. Hoi
P2pdoctagger: Content Management Through Automated P2p Collaborative Tagging, Hock Hee Ang, Vivekanand Gopalkrishnan, Wee Keong Ng, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
As the amount of user generated content grows, personal information management has become a challenging problem. Several information management approaches, such as desktop search, document organization and (collaborative) document tagging have been proposed to address this, however they are either inappropriate or inefficient. Automated collaborative document tagging approaches mitigate the problems of manual tagging, but they are usually based on centralized settings which are plagued by problems such as scalability, privacy, etc. To resolve these issues, we present P2PDocTagger, an automated and distributed document tagging system based on classification in P2P networks. P2P-DocTagger minimizes the efforts of individual peers and …
A Hoare Calculus For Graph Programs, Christopher M. Poskitt, Detlef Plump
A Hoare Calculus For Graph Programs, Christopher M. Poskitt, Detlef Plump
Research Collection School Of Computing and Information Systems
We present Hoare-style axiom schemata and inference rules for verifying the partial correctness of programs in the graph programming language GP. The pre- and postconditions of this calculus are the nested conditions of Habel, Pennemann and Rensink, extended with expressions for labels in order to deal with GP’s conditional rule schemata and infinite label alphabet. We show that the proof rules are sound with respect to GP’s operational semantics.
Developing Model Checkers Using Pat, Yang Liu, Jun Sun, Jin Song Dong
Developing Model Checkers Using Pat, Yang Liu, Jun Sun, Jin Song Dong
Research Collection School Of Computing and Information Systems
During the last two decades, model checking has emerged as an effective system analysis technique complementary to simulation and testing. Many model checking algorithms and state space reduction techniques have been proposed. Although it is desirable to have dedicated model checkers for every language (or application domain), implementing one with effective reduction techniques is rather challenging. In this work, we present a generic and extensible framework PAT, which facilitates users to build customized model checkers. PAT provides a library of state-of-art model checking algorithms as well as support for customizing language syntax, semantics, state space reduction techniques, graphic user interfaces, …
Diract: Agent-Based Interactive Storytelling, Yundong Cai, Zhiqi Shen, Chunyan Miao, Ah-Hwee Tan
Diract: Agent-Based Interactive Storytelling, Yundong Cai, Zhiqi Shen, Chunyan Miao, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
A lot of researches haven been done on the interactive storytelling authoring , e.g. by a director agent, or by interactions among a number of character agents. However, it is still difficult to construct the interactive storytelling for novice users, due to a need of various agents development and complex communication among the agents. We propose an agent-based interactive storytelling architecture, namely DIRACT (short of “Direct and Act”). It is composed of numerous atomic DIRACT agents, which are goal oriented and use an unified communication protocol. By removing the difference between the director and character, each DIRACT agent can either …
On Challenges In Evaluating Malware Clustering, Peng Li, Limin Liu, Debin Gao, Michael K Reiter
On Challenges In Evaluating Malware Clustering, Peng Li, Limin Liu, Debin Gao, Michael K Reiter
Research Collection School Of Computing and Information Systems
Malware clustering and classification are important tools that enable analysts to prioritize their malware analysis efforts. The recent emergence of fully automated methods for malware clustering and classification that report high accuracy suggests that this problem may largely be solved. In this paper, we report the results of our attempt to confirm our conjecture that the method of selecting ground-truth data in prior evaluations biases their results toward high accuracy. To examine this conjecture, we apply clustering algorithms from a different domain (plagiarism detection), first to the dataset used in a prior work's evaluation and then to a wholly new …
Comprehensive Evaluation Of Association Measures For Fault Localization, Lucia Lucia, David Lo, Lingxiao Jiang, Aditya Budi
Comprehensive Evaluation Of Association Measures For Fault Localization, Lucia Lucia, David Lo, Lingxiao Jiang, Aditya Budi
Research Collection School Of Computing and Information Systems
In statistics and data mining communities, there have been many measures proposed to gauge the strength of association between two variables of interest, such as odds ratio, confidence, Yule-Y, Yule-Q, Kappa, and gini index. These association measures have been used in various domains, for example, to evaluate whether a particular medical practice is associated positively to a cure of a disease or whether a particular marketing strategy is associated positively to an increase in revenue, etc. This paper models the problem of locating faults as association between the execution or non-execution of particular program elements with failures. There have been …
An Automated Approach For Finding Variable-Constant Pairing Bugs, Julia Lawall, David Lo
An Automated Approach For Finding Variable-Constant Pairing Bugs, Julia Lawall, David Lo
Research Collection School Of Computing and Information Systems
Named constants are used heavily in operating systems code, both as internal flags and in interactions with devices. Decision making within an operating system thus critically depends on the correct usage of these values. Nevertheless, compilers for the languages typically used in implementing operating systems provide little support for checking the usage of named constants. This affects correctness, when a constant is used in a context where its value is meaningless, and software maintenance, when a constant has the right value for its usage context but the wrong name. We propose a hybrid program-analysis and data-mining based approach to identify …
Embellishing Text Search Queries To Protect User Privacy, Hwee Hwa Pang, Xuhua Ding, Xiaokui Xiao
Embellishing Text Search Queries To Protect User Privacy, Hwee Hwa Pang, Xuhua Ding, Xiaokui Xiao
Research Collection School Of Computing and Information Systems
Users of text search engines are increasingly wary that their activities may disclose confidential information about their business or personal profiles. It would be desirable for a search engine to perform document retrieval for users while protecting their intent. In this paper, we identify the privacy risks arising from semantically related search terms within a query, and from recurring highspecificity query terms in a search session. To counter the risks, we propose a solution for a similarity text retrieval system to offer anonymity and plausible deniability for the query terms, and hence the user intent, without degrading the system’s precision-recall …
Context-Aware Query Recommendations, Alexandros Ntoulas, Heasoo Hwang, Lise Getoor, Stelios Paparizos, Hady Wirawan Lauw
Context-Aware Query Recommendations, Alexandros Ntoulas, Heasoo Hwang, Lise Getoor, Stelios Paparizos, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Described is a search-related technology in which context information regarding a user's prior search actions is used in making query recommendations for a current user action, such as a query or click. To determine whether each set or subset of context information is relevant to the user action, data obtained from a query log is evaluated. More particularly, a query transition (query-query) graph and a query click (query-URL) graph are extracted from the query log; vectors are computed for the current action and each context/sub-context and evaluated against vectors in the graphs to determine current action-to-context similarity. Also described is …
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval And Clustering, Steven C. H. Hoi, Wei Liu, Shih-Fu Chang
Semi-Supervised Distance Metric Learning For Collaborative Image Retrieval And Clustering, Steven C. H. Hoi, Wei Liu, Shih-Fu Chang
Research Collection School Of Computing and Information Systems
Learning a good distance metric plays a vital role in many multimedia retrieval and data mining tasks. For example, a typical content-based image retrieval (CBIR) system often relies on an effective distance metric to measure similarity between any two images. Conventional CBIR systems simply adopting Euclidean distance metric often fail to return satisfactory results mainly due to the well-known semantic gap challenge. In this article, we present a novel framework of Semi-Supervised Distance Metric Learning for learning effective distance metrics by exploring the historical relevance feedback log data of a CBIR system and utilizing unlabeled data when log data are …
Effect Of Human Biases On Human-Agent Teams, Praveen Paruchuri, Pradeep Reddy Varakantham, Katia Sycara, Paul Scerri
Effect Of Human Biases On Human-Agent Teams, Praveen Paruchuri, Pradeep Reddy Varakantham, Katia Sycara, Paul Scerri
Research Collection School Of Computing and Information Systems
As human-agent teams get increasingly deployed in the real-world, agent designers need to take into account that humans and agents have different abilities to specify preferences. In this paper, we focus on how human biases in specifying preferences for resources impacts the performance of large, heterogeneous teams. In particular, we model the inclination of humans to simplify their preference functions and to exaggerate their utility for desired resources, and show the effect of these biases on the team performance. We demonstrate this on two different problems, which are representative of many resource allocation problems addressed in literature. In both these …
Architectural Strategy For Digital Platforms: Technological And Organizational Perspectives, Jason Woodard, Joel West
Architectural Strategy For Digital Platforms: Technological And Organizational Perspectives, Jason Woodard, Joel West
Research Collection School Of Computing and Information Systems
different spatial queries such as kNN query, range query and CNN query. A comprehensive experimental study has been conducted to
On The Annotation Of Web Videos By Efficient Near-Duplicate Search, Wan-Lei Zhao, Xiao Wu, Chong-Wah Ngo
On The Annotation Of Web Videos By Efficient Near-Duplicate Search, Wan-Lei Zhao, Xiao Wu, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
With the proliferation of Web 2.0 applications, usersupplied social tags are commonly available in social media as a means to bridge the semantic gap. On the other hand, the explosive expansion of social web makes an overwhelming number of web videos available, among which there exists a large number of near-duplicate videos. In this paper, we investigate techniques which allow effective annotation of web videos from a data-driven perspective. A novel classifier-free video annotation framework is proposed by first retrieving visual duplicates and then suggesting representative tags. The significance of this paper lies in the addressing of two timely issues …
Automatic Generation Of Semantic Fields For Annotating Web Images, Gang Wang, Tat Seng Chua, Chong-Wah Ngo, Yong Cheng Wang
Automatic Generation Of Semantic Fields For Annotating Web Images, Gang Wang, Tat Seng Chua, Chong-Wah Ngo, Yong Cheng Wang
Research Collection School Of Computing and Information Systems
The overwhelming amounts of multimedia contents have triggered the need for automatically detecting the semantic concepts within the media contents. With the development of photo sharing websites such as Flickr, we are able to obtain millions of images with usersupplied tags. However, user tags tend to be noisy, ambiguous and incomplete. In order to improve the quality of tags to annotate web images, we propose an approach to build Semantic Fields for annotating the web images. The main idea is that the images are more likely to be relevant to a given concept, if several tags to the image belong …
On Decision Support For Deliberating With Constraints In Constrained Optimization Models, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau, David H. Wood
On Decision Support For Deliberating With Constraints In Constrained Optimization Models, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau, David H. Wood
Research Collection School Of Computing and Information Systems
This paper introduces the Deliberation Decision Support System (DDSS). The DDSS obtains heuristically (using a genetic algorithm) solutions of interest for constrained optimization models. This is illustrated, without loss of generality, by generalized assignment problems. The DDSS also provides users with graphical tools that support post-solution deliberation for constrained optimization models. The DDSS and this paper, as befits practical concerns, are focused on deliberation with respect to the constraints of the models being used.
An Efficient Signcryption Scheme With Key Privacy And Its Extension To Ring Signcryption, Chung Ki Li, Guomin Yang, Duncan S. Wong, Xiaotie Deng, Sherman S. M. Chow
An Efficient Signcryption Scheme With Key Privacy And Its Extension To Ring Signcryption, Chung Ki Li, Guomin Yang, Duncan S. Wong, Xiaotie Deng, Sherman S. M. Chow
Research Collection School Of Computing and Information Systems
In Information Processing Letters (2006), Tan pointed out that the anonymous signcryption scheme proposed by Yang, Wong and Deng (YWD) in ISC 2005 provides neither confidentiality nor anonymity. However, no discussion has been made on how a secure scheme can be made and there is no secure scheme available to date. In this paper, we propose a modification of YWD scheme which resolves the security issues of the original scheme without sacrificing its high efficiency and simple design. Indeed, we show that our scheme achieves confidentiality, existential unforgeability and anonymity with more precise reduction bounds. We also give a variation …
Decentralized Resource Allocation And Scheduling Via Walrasian Auctions With Negotiable Agents, Huaxing Chen, Hoong Chuin Lau
Decentralized Resource Allocation And Scheduling Via Walrasian Auctions With Negotiable Agents, Huaxing Chen, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
This paper is concerned with solving decentralized resource allocation and scheduling problems via auctions with negotiable agents by allowing agents to switch their bid generation strategies within the auction process, such that a better system wide performance is achieved on average as compared to the conventional walrasian auction running with agents of fixed bid generation strategy. We propose a negotiation mechanism embedded in auctioneer to solicit bidders’ change of strategies in the process of auction. Finally we benchmark our approach against conventional auctions subject to the real-time large-scale dynamic resource coordination problem to demonstrate the effectiveness of our approach.
Investigating Perceptions Of A Location-Based Annotation System, Huynh Nhu Hop Quach, Khasfariyati Razikin, Dion Hoe-Lian Goh, Thi Nhu Quynh Kim, Tan Phat Pham, Yin-Leng Theng, Ee-Peng Lim
Investigating Perceptions Of A Location-Based Annotation System, Huynh Nhu Hop Quach, Khasfariyati Razikin, Dion Hoe-Lian Goh, Thi Nhu Quynh Kim, Tan Phat Pham, Yin-Leng Theng, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
We introduce MobiTOP, a Web-based system for organizing and retrieving hierarchical location-based annotations. Each annotation contains multimedia content (such as text, images, video) associated with a location, and users are able to annotate existing annotations to an arbitrary depth, in effect creating a hierarchy. An evaluation was conducted on a group of potential users to ascertain their perceptions of the usability of the application. The results were generally positive and the majority of the participants saw MobiTOP as a useful platform to share location-based information. We conclude with implications of our work and opportunities for future research.
A Probabilistic Approach To Personalized Tag Recommendation, Meiqun Hu, Ee Peng Lim, Jing Jiang
A Probabilistic Approach To Personalized Tag Recommendation, Meiqun Hu, Ee Peng Lim, Jing Jiang
Research Collection School Of Computing and Information Systems
In this work, we study the task of personalized tag recommendation in social tagging systems. To reach out to tags beyond the existing vocabularies of the query resource and of the query user, we examine recommendation methods that are based on personomy translation, and propose a probabilistic framework for incorporating translations by similar users (neighbors). We propose to use distributional divergence to measure the similarity between users in the context of personomy translation, and examine two variations of such similarity measures. We evaluate the proposed framework on a benchmark dataset collected from BibSonomy, and compare with personomy translation methods based …
The Bi-Objective Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau
The Bi-Objective Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Physician scheduling is the assignment of physicians to perform different duties in the hospital timetable. In this paper, the goals are to satisfy as many physicians’ preferences and duty requirements as possible while ensuring optimum usage of available resources. We present a mathematical programming model to represent the problem as a bi-objective optimization problem. Three different methods based on ε–Constraint Method, Weighted-Sum Method and HillClimbing algorithm are proposed. These methods were tested on a real case from the Surgery Department of a large local government hospital, as well as on randomly generated problem instances. The strengths and weaknesses of the …
A New Hardware-Assisted Pir With O(N) Shuffle Cost, Xuhua Ding, Yanjiang Yang, Robert H. Deng, Shuhong Wang
A New Hardware-Assisted Pir With O(N) Shuffle Cost, Xuhua Ding, Yanjiang Yang, Robert H. Deng, Shuhong Wang
Research Collection School Of Computing and Information Systems
Since the concept of private information retrieval (PIR) was first formalized by Chor et al., various constructions have been proposed with a common goal of reducing communication complexity. Unfortunately, none of them is suitable for practical settings mainly due to the prohibitively high cost for either communications or computations. The booming of the Internet and its applications, especially, the recent trend in outsourcing databases, fuels the research on practical PIR schemes. In this paper, we propose a hardware-assisted PIR scheme with a novel shuffle algorithm. Our PIR construction entails O(n) offline computation cost, and constant online operations and O(log n) …
A Decision Theoretic Approach To Data Leakage Prevention, Janusz Marecki, Mudhakar Srivastava, Pradeep Reddy Varakantham
A Decision Theoretic Approach To Data Leakage Prevention, Janusz Marecki, Mudhakar Srivastava, Pradeep Reddy Varakantham
Research Collection School Of Computing and Information Systems
In both the commercial and defense sectors a compelling need is emerging for rapid, yet secure, dissemination of information. In this paper we address the threat of information leakage that often accompanies such information flows. We focus on domains with one information source (sender) and many information sinks (recipients) where: (i) sharing is mutually beneficial for the sender and the recipients, (ii) leaking a shared information is beneficial to the recipients but undesirable to the sender, and (iii) information sharing decisions of the sender are determined using imperfect monitoring of the (un)intended information leakage by the recipients.We make two key …
Messaging Behavior Modeling In Mobile Social Networks, Byung-Won On, Ee Peng Lim, Jing Jiang, Freddy Tat Chua Chua, Viet-An Nguyen, Loo Nin Teow
Messaging Behavior Modeling In Mobile Social Networks, Byung-Won On, Ee Peng Lim, Jing Jiang, Freddy Tat Chua Chua, Viet-An Nguyen, Loo Nin Teow
Research Collection School Of Computing and Information Systems
Mobile social networks are gaining popularity with the pervasive use of mobile phones and other handheld devices. In these networks, users maintain friendship links, exchange short messages and share content with one another. In this paper, we study the user behaviors in mobile messaging and friendship linking using the data collected from a large mobile social network service known as myGamma (m.mygamma.com). We distinguish two types of user behaviors: soliciting active responses for an initiated message and responding to an incoming message. We propose various models for the two behaviors also known as engagingness and responsiveness. Our experiments show that …
Distributed Route Planning And Scheduling Via Hybrid Conflict Resolution, Ramesh Thangarajoo, Hoong Chuin Lau
Distributed Route Planning And Scheduling Via Hybrid Conflict Resolution, Ramesh Thangarajoo, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper, we discuss the problem of route planning and scheduling by a group of agents. Each agent is responsible for designing a route plan and schedule over a geographical network, and the goal is to obtain a conflict-free plan/schedule that optimizes a global objective. We present a hybrid conflict resolution method that involves coalition formation and distributed constraint satisfaction depending on the level of coupling between agents. We show how this approach can be effectively applied to solve a distributed convoy movement planning problem.
Team Performance Prediction In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Jaideep Srivastava
Team Performance Prediction In Massively Multiplayer Online Role-Playing Games (Mmorpgs), Kyong Jin Shim, Jaideep Srivastava
Research Collection School Of Computing and Information Systems
In this study, we propose a comprehensive performance management tool for measuring and reporting operational activities of teams. This study uses performance data of game players and teams in EverQuest II, a popular MMORPG developed by Sony Online Entertainment, to build performance prediction models for task performing teams. The prediction models provide a projection of task performing team's future performance based on the past performance patterns of participating players on the team as well as team characteristics. While the existing game system lacks the ability to predict team-level performance, the prediction models proposed in this study are expected to be …
Learning Personal Agents With Adaptive Player Modeling In Virtual Worlds, Yilin Kang, Ah-Hwee Tan
Learning Personal Agents With Adaptive Player Modeling In Virtual Worlds, Yilin Kang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
There has been growing interest in creating intelligent agents in virtual worlds that do not follow fixed scripts predefined by the developers, but react accordingly based on actions performed by human players during their interaction. In order to achieve this objective, previous approaches have attempted to model the environment and the user’s context directly. However, a critical component for enabling personalized virtual world experience is missing, namely the capability to adapt over time to the habits and eccentricity of a particular player. To address the above issue, this paper presents a cognitive agent with learning player model capability for personalized …