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Articles 3211 - 3240 of 4266
Full-Text Articles in Entire DC Network
Predicting Common Web Application Vulnerabilities From Input Validation And Sanitization Code Patterns, Lwin Khin Shar, Hee Beng Kuan Tan
Predicting Common Web Application Vulnerabilities From Input Validation And Sanitization Code Patterns, Lwin Khin Shar, Hee Beng Kuan Tan
Research Collection School Of Computing and Information Systems
Software defect prediction studies have shown that defect predictors built from static code attributes are useful and effective. On the other hand, to mitigate the threats posed by common web application vulnerabilities, many vulnerability detection approaches have been proposed. However, finding alternative solutions to address these risks remains an important research problem. As web applications generally adopt input validation and sanitization routines to prevent web security risks, in this paper, we propose a set of static code attributes that represent the characteristics of these routines for predicting the two most common web application vulnerabilities—SQL injection and cross site scripting. In …
Scalable Content Authentication In H.264/Svc Videos Using Perceptual Hashing Based On Dempster-Shafer Theory, Dengpan Ye, Zhuo Wei, Xuhua Ding, Robert H. Deng
Scalable Content Authentication In H.264/Svc Videos Using Perceptual Hashing Based On Dempster-Shafer Theory, Dengpan Ye, Zhuo Wei, Xuhua Ding, Robert H. Deng
Research Collection School Of Computing and Information Systems
The content authenticity of the multimedia delivery is important issue with rapid development and widely used of multimedia technology. Till now many authentication solutions had been proposed, such as cryptology and watermarking based methods. However, in latest heterogeneous network the video stream transmission has b een coded in scalable way such as H.264/SVC, there is still no good authentication solution. In this paper, we firstly summarized related works and p roposed a scalable content authentication scheme using a ratio of different energy (RDE) based perceptual hashing in Q/S dimension, which is used Dempster-Shafer theory and combined with the latest scalable …
The Fat Thumb: Using The Thumb's Contact Size For Single-Handed Mobile Interaction, Sebastian Boring, David Ledo, Xiang ‘Anthony’ Chen, Nicolai Marquardt, Anthony Tang, Saul Greenberg
The Fat Thumb: Using The Thumb's Contact Size For Single-Handed Mobile Interaction, Sebastian Boring, David Ledo, Xiang ‘Anthony’ Chen, Nicolai Marquardt, Anthony Tang, Saul Greenberg
Research Collection School Of Computing and Information Systems
Modern mobile devices allow a rich set of multi-finger interactions that combine modes into a single fluid act, for example, one finger for panning blending into a two-finger pinch gesture for zooming. Such gestures require the use of both hands: one holding the device while the other is interacting. While on the go, however, only one hand may be available to both hold the device and interact with it. This mostly limits interaction to a single-touch (i.e., the thumb), forcing users to switch between input modes explicitly. In this paper, we contribute the Fat Thumb interaction technique, which uses the …
Kbe-Anonymity: Test Data Anonymization For Evolving Programs, Lucia Lucia, David Lo, Lingxiao Jiang, Aditya Budi
Kbe-Anonymity: Test Data Anonymization For Evolving Programs, Lucia Lucia, David Lo, Lingxiao Jiang, Aditya Budi
Research Collection School Of Computing and Information Systems
High-quality test data that is useful for effective testing is often available on users’ site. However, sharing data owned by users with software vendors may raise privacy concerns. Techniques are needed to enable data sharing among data owners and the vendors without leaking data privacy. Evolving programs bring additional challenges because data may be shared multiple times for every version of a program. When multiple versions of the data are cross-referenced, private information could be inferred. Although there are studies addressing the privacy issue of data sharing for testing and debugging, little work has explicitly addressed the challenges when programs …
A Computational Analysis Of Bundle Trading Markets Design For Distributed Resource Allocation, Zhiling Guo, Gary J. Koehler, Andrew B. Whinston
A Computational Analysis Of Bundle Trading Markets Design For Distributed Resource Allocation, Zhiling Guo, Gary J. Koehler, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
Online auction markets play increasingly important roles for resource allocations in distributed systems. This paper builds upon a market-based framework presented by Guo et al. (Guo, Z., G. J. Koehler, A. B. Whinston. 2007. A market-based optimization algorithm for distributed systems. Management Sci. 53(8) 1345–1458), where a distributed system optimization problem is solved by self-interested agents iteratively trading bundled resources in a double auction market run by a dealer. We extend this approach to a dynamic, asynchronous Internet market environment and investigate how various market design factors including dealer inventory policies, market communication patterns, and agent learning strategies affect the …
Verification Of Graph Programs, Christopher M. Poskitt
Verification Of Graph Programs, Christopher M. Poskitt
Research Collection School Of Computing and Information Systems
GP (for Graph Programs) is an experimental nondeterministic programming language which allows for the manipulation of graphs at a high level of abstraction. The program states of GP are directed labelled graphs. These are manipulated directly via the application of (conditional) rule schemata, which generalise double-pushout rules with expressions over labels and relabelling. In contrast with graph grammars, the application of these rule schemata is directed by a number of simple control constructs including sequential composition, conditionals, and as-long-as-possible iteration. GP shields programmers at all times from low-level implementation issues (e.g. graph representation), and with its nondeterministic semantics, allows one …
Interactive Fault Localization Leveraging Simple User Feedback, Liang Gong, David Lo, Lingxiao Jiang, Hongyu Zhang
Interactive Fault Localization Leveraging Simple User Feedback, Liang Gong, David Lo, Lingxiao Jiang, Hongyu Zhang
Research Collection School Of Computing and Information Systems
Millions of people, including those in the software engineering communities have turned to microblogging services, such as Twitter, as a means to quickly disseminate information. A number of past studies by Treude et al., Storey, and Yuan et al. have shown that a wealth of interesting information is stored in these microblogs. However, microblogs also contain a large amount of noisy content that are less relevant to software developers in engineering software systems. In this work, we perform a preliminary study to investigate the feasibility of automatic classification of microblogs into two categories: relevant and irrelevant to engineering software systems. …
In-Game Action List Segmentation And Labeling In Real-Time Strategy Games, Wei Gong, Ee-Peng Lim, Palakorn Achananuparp, Feida Zhu, David Lo, Freddy Chong-Tat Chua
In-Game Action List Segmentation And Labeling In Real-Time Strategy Games, Wei Gong, Ee-Peng Lim, Palakorn Achananuparp, Feida Zhu, David Lo, Freddy Chong-Tat Chua
Research Collection School Of Computing and Information Systems
In-game actions of real-time strategy (RTS) games are extremely useful in determining the players' strategies, analyzing their behaviors and recommending ways to improve their play skills. Unfortunately, unstructured sequences of in-game actions are hardly informative enough for these analyses. The inconsistency we observed in human annotation of in-game data makes the analytical task even more challenging. In this paper, we propose an integrated system for in-game action segmentation and semantic label assignment based on a Conditional Random Fields (CRFs) model with essential features extracted from the in-game actions. Our experiments demonstrate that the accuracy of our solution can be as …
Verifying Total Correctness Of Graph Programs, Christopher M. Poskitt, Detlef Plump
Verifying Total Correctness Of Graph Programs, Christopher M. Poskitt, Detlef Plump
Research Collection School Of Computing and Information Systems
GP 2 is an experimental nondeterministic programming language based on graph transformation rules, allowing for visual programming and the solving of graph problems at a high-level of abstraction. In previous work we demonstrated how to verify graph programs using a Hoare-style proof calculus, but only partial correctness was considered. In this paper, we add new proof rules and termination functions, which allow for proofs to additionally guarantee that program executions always terminate (weak total correctness), or that programs always terminate and do so without failure (total correctness). We show that the new proof rules are sound with respect to the …
Duplicate Bug Report Detection With A Combination Of Information Retrieval And Topic Modeling, Anh Tuan Nguyen, Tung Nguyen, Tien Nguyen, David Lo, Chengnian Sun
Duplicate Bug Report Detection With A Combination Of Information Retrieval And Topic Modeling, Anh Tuan Nguyen, Tung Nguyen, Tien Nguyen, David Lo, Chengnian Sun
Research Collection School Of Computing and Information Systems
Detecting duplicate bug reports helps reduce triaging efforts and save time for developers in fixing the same issues. Among several automated detection approaches, text-based information retrieval (IR) approaches have been shown to outperform others in term of both accuracy and time efficiency. However, those IR-based approaches do not detect well the duplicate reports on the same technical issues written in different descriptive terms. This paper introduces DBTM, a duplicate bug report detection approach that takes advantage of both IR-based features and topic-based features. DBTM models a bug report as a textual document describing certain technical issue(s), and models duplicate bug …
Automatic Classification Of Software Related Microblogs, Philips Kokoh Prasetyo, David Lo, Achananuparp Palakorn, Yuan Tian, Ee Peng Lim
Automatic Classification Of Software Related Microblogs, Philips Kokoh Prasetyo, David Lo, Achananuparp Palakorn, Yuan Tian, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Millions of people, including those in the software engineering communities have turned to microblogging services, such as Twitter, as a means to quickly disseminate information. A number of past studies by Treude et al., Storey, and Yuan et al. have shown that a wealth of interesting information is stored in these microblogs. However, microblogs also contain a large amount of noisy content that are less relevant to software developers in engineering software systems. In this work, we perform a preliminary study to investigate the feasibility of automatic classification of microblogs into two categories: relevant and irrelevant to engineering software systems. …
Diversity Maximization Speedup For Fault Localization, Liang Gong, David Lo, Lingxiao Jiang, Hongyu Zhang
Diversity Maximization Speedup For Fault Localization, Liang Gong, David Lo, Lingxiao Jiang, Hongyu Zhang
Research Collection School Of Computing and Information Systems
Fault localization is useful for reducing debugging effort. However, many fault localization techniques require non-trivial number of test cases with oracles, which can determine whether a program behaves correctly for every test input. Test oracle creation is expensive because it can take much manual labeling effort. Given a number of test cases to be executed, it is challenging to minimize the number of test cases requiring manual labeling and in the meantime achieve good fault localization accuracy. To address this challenge, this paper presents a novel test case selection strategy based on Diversity Maximization Speedup (DMS). DMS orders a set …
To What Extent Could We Detect Field Defects? An Empirical Study Of False Negatives In Static Bug Finding Tools, Ferdian Thung, Lucia Lucia, David Lo, Lingxiao Jiang, Premkumar Devanbu, Foyzur Rahman
To What Extent Could We Detect Field Defects? An Empirical Study Of False Negatives In Static Bug Finding Tools, Ferdian Thung, Lucia Lucia, David Lo, Lingxiao Jiang, Premkumar Devanbu, Foyzur Rahman
Research Collection School Of Computing and Information Systems
Software defects can cause much loss. Static bug-finding tools are believed to help detect and remove defects. These tools are designed to find programming errors; but, do they in fact help prevent actual defects that occur in the field and reported by users? If these tools had been used, would they have detected these field defects, and generated warnings that would direct programmers to fix them? To answer these questions, we perform an empirical study that investigates the effectiveness of state-of-the-art static bug finding tools on hundreds of reported and fixed defects extracted from three open source programs: Lucene, Rhino, …
Reputation As Public Policy For Internet Security, Leigh L. Linden, John S. Quarterman, Qian Tang, Andrew B. Whinston
Reputation As Public Policy For Internet Security, Leigh L. Linden, John S. Quarterman, Qian Tang, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
Insufficient resource allocation causes an Internet information security (infosec) problem that public policy could improve. Lack of transparency lets organizations avoid addressing internal risks, leaving vulnerabilities that are exploited by botnets, threatening information security of other Internet participants. Their protection provides no economic benefit to the firm, so this negative externality causes underinvestment in infosec. Public policy could provide a partial solution by adding incentives for organizations to have well-configured infosec. Specifically, mandatory reporting of security issues plus presenting this information to the public, can impose shame and fame on organizations through publicity and peer influence by comparison with major …
Defeating Sql Injection, Lwin Khin Shar, Hee Beng Kuan Tan
Defeating Sql Injection, Lwin Khin Shar, Hee Beng Kuan Tan
Research Collection School Of Computing and Information Systems
The best strategy for combating SQL injection, which has emerged as the most widespread website security risk, calls for integrating defensive coding practices with both vulnerability detection and runtime attack prevention methods.
A Secure And Efficient Discovery Service System In Epcglobal Network, Jie Shi, Yingjiu Li, Robert H. Deng
A Secure And Efficient Discovery Service System In Epcglobal Network, Jie Shi, Yingjiu Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
In recent years, the Internet of Things (IOT) has drawn considerable attention from the industrial and research communities. Due to the vast amount of data generated through IOT devices and users, there is an urgent need for an effective search engine to help us make sense of this massive amount of data. With this motivation, we begin our initial works on developing a secure and efficient search engine (SecDS) based on EPC Discovery Services (EPCDS) for EPCglobal network, an integral part of IOT. SecDS is designed to provide a bridge between different partners of supply chains to share information while …
Modeling Concept Dynamics For Large Scale Music Search, Jialie Shen, Hwee Hwa Pang, Meng Wang, Shuicheng Yan
Modeling Concept Dynamics For Large Scale Music Search, Jialie Shen, Hwee Hwa Pang, Meng Wang, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Continuing advances in data storage and communication technologies have led to an explosive growth in digital music collections. To cope with their increasing scale, we need effective Music Information Retrieval (MIR) capabilities like tagging, concept search and clustering. Integral to MIR is a framework for modelling music documents and generating discriminative signatures for them. In this paper, we introduce a multimodal, layered learning framework called DMCM. Distinguished from the existing approaches that encode music as an ensemble of order-less feature vectors, our framework extracts from each music document a variety of acoustic features, and translates them into low-level encodings over …
Confidence-Aware Graph Regularization With Heterogeneous Pairwise Features, Yuan Fang, Bo-June Paul Hsu, Kevin Chen-Chuan Chang
Confidence-Aware Graph Regularization With Heterogeneous Pairwise Features, Yuan Fang, Bo-June Paul Hsu, Kevin Chen-Chuan Chang
Research Collection School Of Computing and Information Systems
Conventional classification methods tend to focus on features of individual objects, while missing out on potentially valuable pairwise features that capture the relationships between objects. Although recent developments on graph regularization exploit this aspect, existing works generally assume only a single kind of pairwise feature, which is often insufficient. We observe that multiple, heterogeneous pairwise features can often complement each other and are generally more robust in modeling the relationships between objects. Furthermore, as some objects are easier to classify than others, objects with higher initial classification confidence should be weighed more towards classifying related but more ambiguous objects, an …
Boosting Multi-Kernel Locality-Sensitive Hashing For Scalable Image Retrieval, Hao Xia, Steven C. H. Hoi, Pengcheng Wu, Rong Jin
Boosting Multi-Kernel Locality-Sensitive Hashing For Scalable Image Retrieval, Hao Xia, Steven C. H. Hoi, Pengcheng Wu, Rong Jin
Research Collection School Of Computing and Information Systems
Similarity search is a key challenge for multimedia retrieval applications where data are usually represented in high-dimensional space. Among various algorithms proposed for similarity search in high-dimensional space, Locality-Sensitive Hashing (LSH) is the most popular one, which recently has been extended to Kernelized Locality-Sensitive Hashing (KLSH) by exploiting kernel similarity for better retrieval efficacy. Typically, KLSH works only with a single kernel, which is often limited in real-world multimedia applications, where data may originate from multiple resources or can be represented in several different forms. For example, in content-based multimedia retrieval, a variety of features can be extracted to represent …
A Non-Parametric Visual-Sense Model Of Images: Extending The Cluster Hypothesis Beyond Text, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia
A Non-Parametric Visual-Sense Model Of Images: Extending The Cluster Hypothesis Beyond Text, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia
Research Collection School Of Computing and Information Systems
The main challenge of a search engine is to find information that are relevant and appropriate. However, this can become difficult when queries are issued using ambiguous words. Rijsbergen first hypothesized a clustering approach for web pages wherein closely associated pages are treated as a semantic group with the same relevance to the query (Rijsbergen 1979). In this paper, we extend Rijsbergen’s cluster hypothesis to multimedia content such as images. Given a user query, the polysemy in the return image set is related to the many possible meanings of the query. We develop a method to cluster the polysemous images …
Automatic Compositional Verification Of Timed Systems, Shang-Wei Lin, Yang Liu, Jun Sun, Jin Song Dong, Étienne André
Automatic Compositional Verification Of Timed Systems, Shang-Wei Lin, Yang Liu, Jun Sun, Jin Song Dong, Étienne André
Research Collection School Of Computing and Information Systems
Specification and verification of real-time systems are important research topics with crucial applications; however, the so-called state space explosion problem often prevents model checking to be used in practice for large systems. In this work, we present a self-contained toolkit to analyze real-time systems specified using event-recording automata (ERAs), which supports system modeling, animated simulation, and fully automatic compositional verification based on learning techniques. Experimental results show that our tool outperforms the state-of-the-art timed model checker.
Adapting Video Delivery Based On Motion Triggered Visual Attention, Hari Kalva, V. Adzic, Lai-Tee Cheok
Adapting Video Delivery Based On Motion Triggered Visual Attention, Hari Kalva, V. Adzic, Lai-Tee Cheok
Research Collection School Of Computing and Information Systems
Cues from human visual system (HVS) can be used for further optimization of compression in modern hybrid video coding platforms. We present work that explores and exploits motion related attentional limitations. Algorithms for exploiting motion triggered attention were developed and compared with MPEG AVC/H.264 encoder with various settings for different bitrate levels. For the sequences with high motion activity our algorithm provides up to 8% bitrate savings.
Sampling And Ontologically Pooling Web Images For Visual Concept Learning, Shiai Zhu, Chong-Wah Ngo, Yu-Gang Jiang
Sampling And Ontologically Pooling Web Images For Visual Concept Learning, Shiai Zhu, Chong-Wah Ngo, Yu-Gang Jiang
Research Collection School Of Computing and Information Systems
Sufficient training examples are essential for effective learning of semantic visual concepts. In practice, however, acquiring noise-free training examples has always been expensive. Recently the rapid popularization of social media websites, such as Flickr, has made it possible to collect training exemplars without human assistance. This paper proposes a novel and efficient approach to collect training samples from the noisily tagged Web images for visual concept learning, where we try to maximize two important criteria, relevancy and coverage, of the automatically generated training sets. For the former, a simple method named semantic field is introduced to handle the imprecise and …
Improved Bdd-Based Discrete Analysis Of Timed Systems, Truong Khanh Nguyen, Jun Sun, Yang Liu, Jin Song Dong, Yan Liu
Improved Bdd-Based Discrete Analysis Of Timed Systems, Truong Khanh Nguyen, Jun Sun, Yang Liu, Jin Song Dong, Yan Liu
Research Collection School Of Computing and Information Systems
Model checking timed systems through digitization is relatively easy, compared to zone-based approaches. The applicability of digitization, however, is limited mainly for two reasons, i.e., it is only sound for closed timed systems; and clock ticks cause state space explosion. The former is mild as many practical systems are subject to digitization. It has been shown that BDD-based techniques can be used to tackle the latter to some extent. In this work, we significantly improve the existing approaches by keeping the ticks simple in the BDD encoding. Taking advantage of the ‘simple’ nature of clock ticks, we fine-tune the encoding …
Shortest Path Computation With No Information Leakage, Kyriakos Mouratidis, Man Lung Yiu
Shortest Path Computation With No Information Leakage, Kyriakos Mouratidis, Man Lung Yiu
Research Collection School Of Computing and Information Systems
Shortest path computation is one of the most common queries in location-based services (LBSs). Although particularly useful, such queries raise serious privacy concerns. Exposing to a (potentially untrusted) LBS the client’s position and her destination may reveal personal information, such as social habits, health condition, shopping preferences, lifestyle choices, etc. The only existing method for privacy-preserving shortest path computation follows the obfuscation paradigm; it prevents the LBS from inferring the source and destination of the query with a probability higher than a threshold. This implies, however, that the LBS still deduces some information (albeit not exact) about the client’s location …
Using Monterey Phoenix To Formalize And Verify System Architectures, Jiexin Zhang, Yang Liu, Mikhail Auguston, Jun Sun, Jin Song Dong
Using Monterey Phoenix To Formalize And Verify System Architectures, Jiexin Zhang, Yang Liu, Mikhail Auguston, Jun Sun, Jin Song Dong
Research Collection School Of Computing and Information Systems
Modeling and analyzing software architectures are useful for helping to understand the system structures and facilitate proper implementation of user requirements. Despite its importance in the software engineering practice, the lack of formal description and verification support hinders the development of quality architectural models. In this work, we develop an approach for modeling and verifying software architectures specified using Monterey Phoenix (MP) architecture description language. Firstly, we formalize the syntax and operational semantics for MP. This language is capable of modeling system and environment behaviors based on event traces, as well as supporting different architecture composition operations and views. Secondly, …
On-Line Portfolio Selection With Moving Average Reversion, Bin Li, Steven C. H. Hoi
On-Line Portfolio Selection With Moving Average Reversion, Bin Li, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
On-line portfolio selection has attracted increasing interests in machine learning and AI communities recently. Empirical evidences show that stock's high and low prices are temporary and stock price relatives are likely to follow the mean reversion phenomenon. While the existing mean reversion strategies are shown to achieve good empirical performance on many real datasets, they often make the single-period mean reversion assumption, which is not always satisfied in some real datasets, leading to poor performance when the assumption does not hold. To overcome the limitation, this article proposes a multiple-period mean reversion, or so-called Moving Average Reversion (MAR), and a …
Formal Analysis Of Pervasive Computing Systems, Yan Liu, Xian Zhang, Jin Song Dong, Yang Liu, Jun Sun, Jit Biswas, Mounir Mokhtari
Formal Analysis Of Pervasive Computing Systems, Yan Liu, Xian Zhang, Jin Song Dong, Yang Liu, Jun Sun, Jit Biswas, Mounir Mokhtari
Research Collection School Of Computing and Information Systems
Pervasive computing systems are heterogenous and complex as they usually involve human activities, various sensors and actuators as well as middleware for system controlling. Therefore, analyzing such systems is highly nontrivial. In this work, we propose to use formal methods for analyzing pervasive computing systems. Firstly, a formal modeling framework is proposed to cover the main characteristics of pervasive computing systems (e.g., context-awareness, concurrent communications, layered architectures). Secondly, we identify the safety requirements (e.g., free of deadlocks and conflicts etc.) and propose their specifications as safety and liveness properties. Finally, we demonstrate our ideas using a case study of a …
Adaptive Cgf For Pilots Training In Air Combat Simulation, Teck-Hou Teng, Ah-Hwee Tan, Wee-Sze Ong, Kien-Lip Lee
Adaptive Cgf For Pilots Training In Air Combat Simulation, Teck-Hou Teng, Ah-Hwee Tan, Wee-Sze Ong, Kien-Lip Lee
Research Collection School Of Computing and Information Systems
Training of combat fighter pilots is often conducted using either human opponents or non-adaptive computer-generated force (CGF) inserted with the doctrine for conducting air combat mission. The novelty and challenges of such non-adaptive doctrine-driven CGF is often lost quickly. Incorporating more complex knowledge manually is known to be tedious and time-consuming. Therefore, a study of using adaptive CGF to learn from the real-time interactions with human pilots to extend the existing doctrine is conducted in this work. The goal of this study is to show how an adaptive CGF can be more effective than a non-adaptive doctrine-driven CGF for simulator-based …
Parameter Synthesis For Hierarchical Concurrent Real-Time Systems, Étienne André, Yang Liu, Jun Sun, Jin Song Dong
Parameter Synthesis For Hierarchical Concurrent Real-Time Systems, Étienne André, Yang Liu, Jun Sun, Jin Song Dong
Research Collection School Of Computing and Information Systems
Modeling and verifying complex real-time systems, involving timing delays, are notoriously difficult problems. Checking the correctness of a system for one particular value for each delay does not give any information for other values. It is hence interesting to reason parametrically, by considering that the delays are parameters (unknown constants) and synthesize a constraint guaranteeing a correct behavior. We present here Parametric Stateful Timed CSP, a language capable of specifying hierarchical real-time systems with complex data structures. Although we prove that the synthesis is undecidable in general, we present an algorithm for efficient parameter synthesis that behaves well in practice.