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Research Collection School Of Computing and Information Systems

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Joint Learning For Coreference Resolution With Markov Logic, Yang Song, Jing Jiang, Xin Zhao, Sujian Li, Houfeng Wang Jul 2012

Joint Learning For Coreference Resolution With Markov Logic, Yang Song, Jing Jiang, Xin Zhao, Sujian Li, Houfeng Wang

Research Collection School Of Computing and Information Systems

Pairwise coreference resolution models must merge pairwise coreference decisions to generate final outputs. Traditional merging methods adopt different strategies such as the best first method and enforcing the transitivity constraint, but most of these methods are used independently of the pairwise learning methods as an isolated inference procedure at the end. We propose a joint learning model which combines pairwise classification and mention clustering with Markov logic. Experimental results show that our joint learning system outperforms independent learning systems. Our system gives a better performance than all the learning-based systems from the CoNLL-2011 shared task on the same dataset. Compared …

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Identifying Event-Related Bursts Via Social Media Activities, Xin Zhao, Baihan Shu, Jing Jiang, Yang Song, Hongfei Yan, Xiaoming Li Jul 2012

Identifying Event-Related Bursts Via Social Media Activities, Xin Zhao, Baihan Shu, Jing Jiang, Yang Song, Hongfei Yan, Xiaoming Li

Research Collection School Of Computing and Information Systems

Activities on social media increase at a dramatic rate. When an external event happens, there is a surge in the degree of activities related to the event. These activities may be temporally correlated with one another, but they may also capture different aspects of an event and therefore exhibit different bursty patterns. In this paper, we propose to identify event-related bursts via social media activities. We study how to correlate multiple types of activities to derive a global bursty pattern. To model smoothness of one state sequence, we propose a novel function which can capture the state context. The experiments …

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Rejoinder: Real-Time Road Traffic Forecasting Using Regime-Switching Space-Time Models And Adaptive Lasso, Yiannis Kamarianakis, Wei Shen, Laura Wynter Jul 2012

Rejoinder: Real-Time Road Traffic Forecasting Using Regime-Switching Space-Time Models And Adaptive Lasso, Yiannis Kamarianakis, Wei Shen, Laura Wynter

Research Collection School Of Computing and Information Systems

Kamarianakis et al. presented a promising application of multivariate time series analysis to the traffic condition forecasting problem in urban transportation networks. Interest is keen and growing in providing accurate predictions of link and route travel conditions, especially in the context of the burgeoning demand for ‘real-time’ traveler information. Forecasts underlying this information must be sufficiently accurate for the traveler information provided to be of tangible value. As the authors clearly pointed out, although the near ubiquitous availability of urban traffic condition data makes area-wide forecasts theoretically possible, scalability to area-wide networks and the required speed of forecast generation represent …

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Enhancing Access Privacy Of Range Retrievals Over B+Trees, Hwee Hwa Pang, Jilian Zhang, Kyriakos Mouratidis Jul 2012

Enhancing Access Privacy Of Range Retrievals Over B+Trees, Hwee Hwa Pang, Jilian Zhang, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Users of databases that are hosted on shared servers cannot take for granted that their queries will not be disclosed to unauthorized parties. Even if the database is encrypted, an adversary who is monitoring the I/O activity on the server may still be able to infer some information about a user query. For the particular case of a B+-tree that has its nodes encrypted, we identify properties that enable the ordering among the leaf nodes to be deduced. These properties allow us to construct adversarial algorithms to recover the B+-tree structure from the I/O traces generated by range queries. Combining …

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Exact Soft Confidence-Weighted Learning, Jialei Wang, Steven C. H. Hoi Jul 2012

Exact Soft Confidence-Weighted Learning, Jialei Wang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

In this paper, we propose a new Soft Confidence-Weighted (SCW) online learning scheme, which enables the conventional confidence-weighted learning method to handle non-separable cases. Unlike the previous confidence-weighted learning algorithms, the proposed soft confidence-weighted learning method enjoys all the four salient properties: (i) large margin training, (ii) confidence weighting, (iii) capability to handle non-separable data, and (iv) adaptive margin. Our experimental results show that the proposed SCW algorithms significantly outperform the original CW algorithm. When comparing with a variety of state-of-the art algorithms (including AROW, NAROW and NHERD), we found that SCW generally achieves better or at least comparable predictive …

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Translating Pddl Into Csp# - The Pat Approach, Yi Li, Jing Sun, Jin Song Dong, Yang Liu, Jun Sun Jul 2012

Translating Pddl Into Csp# - The Pat Approach, Yi Li, Jing Sun, Jin Song Dong, Yang Liu, Jun Sun

Research Collection School Of Computing and Information Systems

Model checking provides a way to automatically verify hardware and software systems, whereas the goal of planning is to produce a sequence of actions that leads from the initial state to the desired goal state. Recently research indicates that there is a strong connection between model checking and planning problem solving. In this paper, we investigate the feasibility of using a newly developed model checking framework, Process Analysis Toolkit (PAT), to serve as a planning solution provider for upper layer applications. We first carried out a number of experiments on different planning tools in order to compare their performance and …

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Real-Time Road Traffic Forecasting Using Regime-Switching Space-Time Models And Adaptive Lasso, Yiannis Kamarianakis, Wei Shen, Laura Wynter Jul 2012

Real-Time Road Traffic Forecasting Using Regime-Switching Space-Time Models And Adaptive Lasso, Yiannis Kamarianakis, Wei Shen, Laura Wynter

Research Collection School Of Computing and Information Systems

Smart transportation technologies require real-time traffic prediction to be both fast and scalable to full urban networks. We discuss a method that is able to meet this challenge while accounting for nonlinear traffic dynamics and space-time dependencies of traffic variables. Nonlinearity is taken into account by a union of non-overlapping linear regimes characterized by a sequence of temporal thresholds. In each regime, for each measurement location, a penalized estimation scheme, namely the adaptive absolute shrinkage and selection operator (LASSO), is implemented to perform model selection and coefficient estimation simultaneously. Both the robust to outliers least absolute deviation estimates and conventional …

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Analyzing Multi-Agent Systems With Probabilistic Model Checking Approach, Songzheng Song, Jianye Hao, Yang Liu, Jun Sun, Ho-Fung Leung, Jin Song Dong Jun 2012

Analyzing Multi-Agent Systems With Probabilistic Model Checking Approach, Songzheng Song, Jianye Hao, Yang Liu, Jun Sun, Ho-Fung Leung, Jin Song Dong

Research Collection School Of Computing and Information Systems

Multi-agent systems, which are composed of autonomous agents, have been successfully employed as a modeling paradigm in many scenarios. However, it is challenging to guarantee the correctness of their behaviors due to the complex nature of the autonomous agents, especially when they have stochastic characteristics. In this work, we propose to apply probabilistic model checking to analyze multi-agent systems. A modeling language called PMA is defined to specify such kind of systems, and LTL property and logic of knowledge combined with probabilistic requirements are supported to analyze system behaviors. Initial evaluation indicates the effectiveness of our current progress; meanwhile some …

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Mining Input Sanitization Patterns For Predicting Sql Injection And Cross Site Scripting Vulnerabilities, Lwin Khin Shar, Hee Beng Kuan Tan Jun 2012

Mining Input Sanitization Patterns For Predicting Sql Injection And Cross Site Scripting Vulnerabilities, Lwin Khin Shar, Hee Beng Kuan Tan

Research Collection School Of Computing and Information Systems

Static code attributes such as lines of code and cyclomatic complexity have been shown to be useful indicators of defects in software modules. As web applications adopt input sanitization routines to prevent web security risks, static code attributes that represent the characteristics of these routines may be useful for predicting web application vulnerabilities. In this paper, we classify various input sanitization methods into different types and propose a set of static code attributes that represent these types. Then we use data mining methods to predict SQL injection and cross site scripting vulnerabilities in web applications. Preliminary experiments show that our …

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Workitemexplorer: Visualizing Software Development Tasks Using An Interactive Exploration Environment, Christoph Treude, Patrick Gorman, Lars Grammel, Margaret-Anne Storey Jun 2012

Workitemexplorer: Visualizing Software Development Tasks Using An Interactive Exploration Environment, Christoph Treude, Patrick Gorman, Lars Grammel, Margaret-Anne Storey

Research Collection School Of Computing and Information Systems

This demo introduces WorkItemExplorer, an interactive environment to visually explore data from software development tasks. WorkItemExplorer enables developers and managers to investigate activity and correlations in their task management system by making data exploration flexible and interactive, and by utilizing multiple coordinated views. Our preliminary evaluation shows that WorkItemExplorer is able to answer questions that developers ask, while also enabling them to gain new insights through the free exploration of data.

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A Biologically-Inspired Affective Model Based On Cognitive Situational Appraisal, Feng Shu, Ah-Hwee Tan Jun 2012

A Biologically-Inspired Affective Model Based On Cognitive Situational Appraisal, Feng Shu, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Although various emotion models have been proposed based on appraisal theories, most of them focus on designing specific appraisal rules and there is no unified framework for emotional appraisal. Moreover, few existing emotion models are biologically-inspired and are inadequate in imitating emotion process of human brain. This paper proposes a bio-inspired computational model called Cognitive Regulated Affective Architecture (CRAA), inspired by the cognitive regulated emotion theory and the network theory of emotion. This architecture is proposed by taking the following positions: (1) Cognition and emotion are not separated but interacted systems; (2) The appraisal of emotion depends on and should …

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Where Should The Bugs Be Fixed? More Accurate Information Retrieval-Based Bug Localization Based On Bug Reports, Jian Zhou, Hongyu Zhang, David Lo Jun 2012

Where Should The Bugs Be Fixed? More Accurate Information Retrieval-Based Bug Localization Based On Bug Reports, Jian Zhou, Hongyu Zhang, David Lo

Research Collection School Of Computing and Information Systems

For a large and evolving software system, the project team could receive a large number of bug reports. Locating the source code files that need to be changed in order to fix the bugs is a challenging task. Once a bug report is received, it is desirable to automatically point out to the files that developers should change in order to fix the bug. In this paper, we propose BugLocator, an information retrieval based method for locating the relevant files for fixing a bug. BugLocator ranks all files based on the textual similarity between the initial bug report and the …

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Mining Quantified Temporal Rules: Formalism, Algorithms, And Evaluation, David Lo, Ganesan Ramalingam, Venkatesh Prasad Ranganath, Kapil Vaswani Jun 2012

Mining Quantified Temporal Rules: Formalism, Algorithms, And Evaluation, David Lo, Ganesan Ramalingam, Venkatesh Prasad Ranganath, Kapil Vaswani

Research Collection School Of Computing and Information Systems

Libraries usually impose constraints on how clients should use them. Often these constraints are not well-documented. In this paper, we address the problem of recovering such constraints automatically, a problem referred to as specification mining. Given some client programs that use a given library, we identify constraints on the library usage that are (almost) satisfied by the given set of clients.The class of rules we target for mining combines simple binary temporal operators with state predicates (composed of equality constraints) and quantification. This is a simple yet expressive subclass of temporal properties (LTL formulae) that allows us to capture many …

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Active Malware Analysis Using Stochastic Games, Simon Williamson, Pradeep Reddy Varakantham, Debin Gao, Chen Hui Ong Jun 2012

Active Malware Analysis Using Stochastic Games, Simon Williamson, Pradeep Reddy Varakantham, Debin Gao, Chen Hui Ong

Research Collection School Of Computing and Information Systems

Cyber security is increasingly important for defending computer systems from loss of privacy or unauthorised use. One important aspect is threat analysis - how does an attacker infiltrate a system and what do they want once they are inside. This paper considers the problem of Active Malware Analysis, where we learn about the human or software intruder by actively interacting with it with the goal of learning about its behaviours and intentions, whilst at the same time that intruder may be trying to avoid detection or showing those behaviours and intentions. This game-theoretic active learning is then used to obtain …

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Identifying Linux Bug Fixing Patches, Yuan Tian, Julia Lawall, David Lo Jun 2012

Identifying Linux Bug Fixing Patches, Yuan Tian, Julia Lawall, David Lo

Research Collection School Of Computing and Information Systems

In the evolution of an operating system there is a continuing tension between the need to develop and test new features, and the need to provide a stable and secure execution environment to users. A compromise, adopted by the developers of the Linux kernel, is to release new versions, including bug fixes and new features, frequently, while maintaining some older “longterm” versions. This strategy raises the problem of how to identify bug fixing patches that are submitted to the current version but should be applied to the longterm versions as well. The current approach is to rely on the individual …

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Trurepec: A Trust-Behavior-Based Reputation And Recommender System For Mobile Applications, Zheng Yan, Peng Zhang, Robert H. Deng Jun 2012

Trurepec: A Trust-Behavior-Based Reputation And Recommender System For Mobile Applications, Zheng Yan, Peng Zhang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Mobile applications are software packages that can be installed and executed in a mobile device. Which mobile application is trustworthy for a user to purchase, download, install, execute or recommend becomes a crucial issue that impacts its final success. This paper proposes TruBeRepec, a trust-behavior-based reputation and recommender system for mobile applications. We explore a model of trust behavior for mobile applications based on the result of a large-scale user survey. We further develop a number of algorithms that are used to evaluate individual user’s trust in a mobile application through trust behavior observation, generate the application’s reputation by aggregating …

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Virtualization Based Password Protection Against Malware In Untrusted Operating Systems, Yueqiang Cheng, Xuhua Ding Jun 2012

Virtualization Based Password Protection Against Malware In Untrusted Operating Systems, Yueqiang Cheng, Xuhua Ding

Research Collection School Of Computing and Information Systems

Password based authentication remains as the mainstream user authentication method for most web servers, despite its known vulnerability to keylogger attacks. Most existing countermeasures are costly because they require a strong isolation of the browser and the operating system. In this paper, we propose KGuard, a password input protection system. Its security is based on the hardware-based virtualization without safeguarding the browser or OS. A security-conscious user can conveniently and securely activate or deactivate the password protection by using key combinations. We have implemented KGuard and experimented our prototype on Windows with Firefox. The results show that no significant performance …

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Active Refinement Of Clone Anomaly Reports, Lucia, David Lo, Lingxiao Jiang, Aditya Budi Jun 2012

Active Refinement Of Clone Anomaly Reports, Lucia, David Lo, Lingxiao Jiang, Aditya Budi

Research Collection School Of Computing and Information Systems

Software clones have been widely studied in the recent literature and shown useful for finding bugs because inconsistent changes among clones in a clone group may indicate potential bugs. However, many inconsistent clone groups are not real bugs (true positives). The excessive number of false positives could easily impede broad adoption of clone-based bug detection approaches. In this work, we aim to improve the usability of clone-based bug detection tools by increasing the rate of true positives found when a developer analyzes anomaly reports. Our idea is to control the number of anomaly reports a user can see at a …

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Stochastic Dominance In Stochastic Dcops For Risk-Sensitive Applications, Nguyen Duc Thien, William Yeoh, Hoong Chuin Lau Jun 2012

Stochastic Dominance In Stochastic Dcops For Risk-Sensitive Applications, Nguyen Duc Thien, William Yeoh, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Distributed constraint optimization problems (DCOPs) are well-suited for modeling multi-agent coordination problems where the primary interactions are between local subsets of agents. However, one limitation of DCOPs is the assumption that the constraint rewards are without uncertainty. Researchers have thus extended DCOPs to Stochastic DCOPs (SDCOPs), where rewards are sampled from known probability distribution reward functions, and introduced algorithms to find solutions with the largest expected reward. Unfortunately, such a solution might be very risky, that is, very likely to result in a poor reward. Thus, in this paper, we make three contributions: (1) we propose a stricter objective for …

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Memory Formation, Consolidation, And Forgetting In Learning Agents, Budhitama Subagdja, Wenwen Wang, Ah-Hwee Tan, Yuan-Sin Tan, Loo-Nin Teow Jun 2012

Memory Formation, Consolidation, And Forgetting In Learning Agents, Budhitama Subagdja, Wenwen Wang, Ah-Hwee Tan, Yuan-Sin Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

Memory enables past experiences to be remembered and acquired as useful knowledge to support decision making, especially when perception and computational resources are limited. This paper presents a neuropsychological-inspired dual memory model for agents, consisting of an episodic memory that records the agent’s experience in real time and a semantic memory that captures factual knowledge through a parallel consolidation process. In addition, the model incorporates a natural forgetting mechanism that prevents memory overloading by removing transient memory traces. Our experimental study based on a real-time first-person-shooter video game has indicated that the memory consolidation and forgetting processes are not only …

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A Self-Organizing Multi-Memory System For Autonomous Agents, Wenwen Wang, Budhitama Subagdja, Ah-Hwee Tan, Yuan-Sin Tan Jun 2012

A Self-Organizing Multi-Memory System For Autonomous Agents, Wenwen Wang, Budhitama Subagdja, Ah-Hwee Tan, Yuan-Sin Tan

Research Collection School Of Computing and Information Systems

This paper presents a self-organizing approach to the learning of procedural and declarative knowledge in parallel using independent but interconnected memory models. The proposed system, employing fusion Adaptive Resonance Theory (fusion ART) network as a building block, consists of a declarative memory module, that learns both episodic traces and semantic knowledge in real time, as well as a procedural memory module that learns reactive responses to its environment through reinforcement learning. More importantly, the proposed multi-memory system demonstrates how the various memory modules transfer knowledge and cooperate with each other for a higher overall performance. We present experimental studies, wherein …

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A New Framework For Privacy Of Rfid Path Authentication, Shaoying Cai, Robert H. Deng, Yingjiu Li, Yunlei Zhao Jun 2012

A New Framework For Privacy Of Rfid Path Authentication, Shaoying Cai, Robert H. Deng, Yingjiu Li, Yunlei Zhao

Research Collection School Of Computing and Information Systems

RFID-based path authentication enables supply chain managers to verify the exact path that a tag has taken. In this paper, we introduce a new oracle Move that models a tag's movement along a designed or an arbitrary path in a supply chain. With this oracle, we refine the existing security and privacy notions for RFID-based path authentication. In addition, we propose a new privacy notion, called path privacy, for RFID-based path authentication. Our privacy notion captures the privacy of both tag identity and path information in a single game. Compared to existing two-game based privacy notions, it is more rigorous, …

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Memory Formation, Consolidation, And Forgetting In Learning Agents, Budhitama Susnagdja, Wenwen Wang, Ah-Hwee Tan, Yuan-Sin Tan, Loo-Nin Teow Jun 2012

Memory Formation, Consolidation, And Forgetting In Learning Agents, Budhitama Susnagdja, Wenwen Wang, Ah-Hwee Tan, Yuan-Sin Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

Memory enables past experiences to be remembered and acquired as useful knowledge to support decision making, especially when perception and computational resources are limited. This paper presents a neuropsychological- inspired dual memory model for agents, consisting of an episodic memory that records the agent's experience in real time and a semantic memory that captures factual knowledge through a parallel consolidation process. In addition, the model incorporates a natural forgetting mechanism that prevents memory overloading by removing transient memory traces. Our experimental study based on a real-time first-person-shooter video game has indicated that the memory consolidation and forgetting processes are not …

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Aligning Images In The Wild, Wen-Yan Lin, Linlin Liu, Yasuyuki Matsushita, Kok-Lim Low, Siying Liu Jun 2012

Aligning Images In The Wild, Wen-Yan Lin, Linlin Liu, Yasuyuki Matsushita, Kok-Lim Low, Siying Liu

Research Collection School Of Computing and Information Systems

Aligning image pairs with significant appearance change is a long standing computer vision challenge. Much of this problem stems from the local patch descriptors’ instability to appearance variation. In this paper we suggest this instability is due less to descriptor corruption and more the difficulty in utilizing local information to canonically define the orientation (scale and rotation) at which a patch’s descriptor should be computed. We address this issue by jointly estimating correspondence and relative patch orientation, within a hierarchical algorithm that utilizes a smoothly varying parameterization of geometric transformations. By collectively estimating the correspondence and orientation of all the …

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Complexity Of The Soundness Problem Of Bounded Workflow Nets, Guan Jun Liu, Jun Sun, Yang Liu, Jin Song Dong Jun 2012

Complexity Of The Soundness Problem Of Bounded Workflow Nets, Guan Jun Liu, Jun Sun, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

Classical workflow nets (WF-nets) are an important class of Petri nets that are widely used to model and analyze workflow systems. Soundness is a crucial property that guarantees these systems are deadlock-free and bounded. Aalst et al. proved that the soundness problem is decidable, and proposed (but not proved) that the soundness problem is EXPSPACE-hard. In this paper, we show that the satisfiability problem of Boolean expression is polynomial time reducible to the liveness problem of bounded WF-nets, and soundness and liveness are equivalent for bounded WF-nets. As a result, the soundness problem of bounded WF-nets is co-NP-hard.Workflow nets with …

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Adaptive Data Acquisition Strategies For Energy-Efficient, Smartphone-Based, Continuous Processing Of Sensor Streams, Lipyeow Lim, Archan Misra, Tianli Mo Jun 2012

Adaptive Data Acquisition Strategies For Energy-Efficient, Smartphone-Based, Continuous Processing Of Sensor Streams, Lipyeow Lim, Archan Misra, Tianli Mo

Research Collection School Of Computing and Information Systems

There is a growing interest in applications that utilize continuous sensing of individual activity or context, via sensors embedded or associated with personal mobile devices (e.g., smartphones). Reducing the energy overheads of sensor data acquisition and processing is essential to ensure the successful continuous operation of such applications, especially on battery-limited mobile devices. To achieve this goal, this paper presents a framework, called ACQUA, for ‘acquisition-cost’ aware continuous query processing. ACQUA replaces the current paradigm, where the data is typically streamed (pushed) from the sensors to the one or more smartphones, with a pull-based asynchronous model, where a smartphone retrieves …

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Are Faults Localizable?, Lucia Lucia, Ferdian Thung, David Lo, Lingxiao Jiang Jun 2012

Are Faults Localizable?, Lucia Lucia, Ferdian Thung, David Lo, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Many fault localization techniques have been proposed to facilitate debugging activities. Most of them attempt to pinpoint the location of faults (i.e., localize faults) based on a set of failing and correct executions and expect debuggers to investigate a certain number of located program elements to find faults. These techniques thus assume that faults are localizable, i.e., only one or a few lines of code that are close to one another are responsible for each fault. However, in reality, are faults localizable? In this work, we investigate hundreds of real faults in several software systems, and find that many faults …

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Coercion Resistance In Authentication Responsibility Shifting, Payas Gupta, Xuhua Ding, Debin Gao May 2012

Coercion Resistance In Authentication Responsibility Shifting, Payas Gupta, Xuhua Ding, Debin Gao

Research Collection School Of Computing and Information Systems

Responsibility shifting, a popular solution used in the event of failure of primary authentication where a human helper is involved in regaining access, is vulnerable to coercion attacks. In this work, we report our user study which investigates the helper’s emotional status when being coerced to assist in an attack. Results show that the coercion causes involuntary skin conductance fluctuation on the helper, which indicates that he/she is nervous and stressed. This response can be used to strengthen the security of the authentication system by providing coercion resistance.

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Spalendar: Visualizing A Group's Calendar Events Over A Geographic Space On A Public Display, Chen Xiang, Sebastian Boring, Sheelagh Carpendale, Anthony Tang, Saul Greenberg May 2012

Spalendar: Visualizing A Group's Calendar Events Over A Geographic Space On A Public Display, Chen Xiang, Sebastian Boring, Sheelagh Carpendale, Anthony Tang, Saul Greenberg

Research Collection School Of Computing and Information Systems

Portable paper calendars (i.e., day planners and organizers) have greatly influenced the design of group electronic calendars. Both use time units (hours/days/weeks/etc.) to organize visuals, with useful information (e.g., event types, locations, attendees) usually presented as - perhaps abbreviated or even hidden - text fields within those time units. The problem is that, for a group, this visual sorting of individual events into time buckets conveys only limited information about the social network of people. For example, people’s whereabouts cannot be read ‘at a glance’ but require examining the text. Our goal is to explore an alternate visualization that can …

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#Epicplay: Crowd-Sourcing Sports Video Highlights, Anthony Tang, Sebastian Boring May 2012

#Epicplay: Crowd-Sourcing Sports Video Highlights, Anthony Tang, Sebastian Boring

Research Collection School Of Computing and Information Systems

During a live sports event, many sports fans use social media as a part of their viewing experience, reporting on their thoughts on the event as it unfolds. In this work, we use this information stream to semantically annotate live broadcast sports games, using these annotations to select video highlights from the game. We demonstrate that this approach can be used to select highlights specific for fans of each team, and that these clips reflect the emotions of a fan during a game. Further, we describe how these clips differ from those seen on nightly sportscasts.

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