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Articles 3331 - 3360 of 4266
Full-Text Articles in Entire DC Network
Differencing Labeled Transition Systems, Zhenchang Xing, Jun Sun, Yang Liu, Jin Song Dong
Differencing Labeled Transition Systems, Zhenchang Xing, Jun Sun, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Concurrent programs often use Labeled Transition Systems (LTSs) as their operational semantic models, which provide the basis for automatic system analysis and verification. System behaviors (generated from the operational semantics) evolve as programs evolve for fixing bugs or implementing new user requirements. Even when a program remains unchanged, its LTS models explored by a model checker or analyzer may be different due to the application of different exploration methods. In this paper, we introduce a novel approach (named SpecDiff) to computing the differences between two LTSs, representing the evolving behaviors of a concurrent program. SpecDiff considers LTSs as Typed Attributed …
Influence Diagrams With Memory States: Representation And Algorithms, Xiaojian Wu, Akshat Kumar, Shlomo Zilberstein
Influence Diagrams With Memory States: Representation And Algorithms, Xiaojian Wu, Akshat Kumar, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
Influence diagrams (IDs) offer a powerful framework for decision making under uncertainty, but their applicability has been hindered by the exponential growth of runtime and memory usage--largely due to the no-forgetting assumption. We present a novel way to maintain a limited amount of memory to inform each decision and still obtain near-optimal policies. The approach is based on augmenting the graphical model with memory states that represent key aspects of previous observations--a method that has proved useful in POMDP solvers. We also derive an efficient EM-based message-passing algorithm to compute the policy. Experimental results show that this approach produces highquality …
An Efficient Algorithm For Learning Event-Recording Automata, Shang-Wei Lin, Étienne André, Jin Song Dong, Jun Sun, Yang Liu
An Efficient Algorithm For Learning Event-Recording Automata, Shang-Wei Lin, Étienne André, Jin Song Dong, Jun Sun, Yang Liu
Research Collection School Of Computing and Information Systems
In inference of untimed regular languages, given an unknown language to be inferred, an automaton is constructed to accept the unknown language from answers to a set of membership queries each of which asks whether a string is contained in the unknown language. One of the most well-known regular inference algorithms is the L* algorithm, proposed by Angluin in 1987, which can learn a minimal deterministic finite automaton (DFA) to accept the unknown language. In this work, we propose an efficient polynomial time learning algorithm, TL*, for timed regular language accepted by event-recording automata. Given an unknown timed regular language, …
Verification Of Orchestration Systems Using Compositional Partial Order Reduction, Tian Huat Tan, Yang Liu, Jun Sun, Jin Song Dong
Verification Of Orchestration Systems Using Compositional Partial Order Reduction, Tian Huat Tan, Yang Liu, Jun Sun, Jin Song Dong
Research Collection School Of Computing and Information Systems
Orc is a computation orchestration language which is designed to specify computational services, such as distributed communication and data manipulation, in a concise and elegant way. Four concurrency primitives allow programmers to orchestrate site calls to achieve a goal, while managing timeouts, priorities, and failures. To guarantee the correctness of Orc model, effective verification support is desirable. Orc has a highly concurrent semantics which introduces the problem of state-explosion to search-based verification methods like model checking. In this paper, we present a new method, called Compositional Partial Order Reduction (CPOR), which aims to provide greater state-space reduction than classic partial …
Prts: An Approach For Model Checking Probabilistic Real-Time Hierarchical Systems, Jun Sun, Yang Liu, Songzheng Song, Jin Song Dong, Xiaohong Li
Prts: An Approach For Model Checking Probabilistic Real-Time Hierarchical Systems, Jun Sun, Yang Liu, Songzheng Song, Jin Song Dong, Xiaohong Li
Research Collection School Of Computing and Information Systems
Model Checking real-life systems is always difficult since such systems usually have quantitative timing factors and work in unreliable environment. The combination of real-time and probability in hierarchical systems presents a unique challenge to system modeling and analysis. In this work, we develop an automated approach for verifying probabilistic, real-time, hierarchical systems. Firstly, a modeling language called PRTS is defined, which combines data structures, real-time and probability. Next, a zone-based method is used to build a finite-state abstraction of PRTS models so that probabilistic model checking could be used to calculate the probability of a system satisfying certain property. We …
Cooperative Reinforcement Learning In Topology-Based Multi-Agent Systems, Dan Xiao, Ah-Hwee Tan
Cooperative Reinforcement Learning In Topology-Based Multi-Agent Systems, Dan Xiao, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Topology-based multi-agent systems (TMAS), wherein agents interact with one another according to their spatial relationship in a network, are well suited for problems with topological constraints. In a TMAS system, however, each agent may have a different state space, which can be rather large. Consequently, traditional approaches to multi-agent cooperative learning may not be able to scale up with the complexity of the network topology. In this paper, we propose a cooperative learning strategy, under which autonomous agents are assembled in a binary tree formation (BTF). By constraining the interaction between agents, we effectively unify the state space of individual …
General Construction Of Chameleon All-But-One Trapdoor Functions, Shengli Liu, Junzuo Lai, Robert H. Deng
General Construction Of Chameleon All-But-One Trapdoor Functions, Shengli Liu, Junzuo Lai, Robert H. Deng
Research Collection School Of Computing and Information Systems
Lossy trapdoor functions enable black-box construction of public key encryption (PKE) schemes secure against chosen-ciphertext attack [18]. Recently, a more efficient black-box construction of public key encryption was given in [12] with the help of chameleon all-but-one trapdoor functions (ABO-TDFs).In this paper, we propose a black-box construction for transforming any ABO-TDFs into chameleon ABO-TDFs with the help of chameleon hash functions. Instantiating the proposed general black-box construction of chameleon ABO-TDFs, we can obtain the first chameleon ABO-TDFs based on the Decisional Diffie-Hellman (DDH) assumption.
Linear Obfuscation To Combat Symbolic Execution, Zhi Wang, Jiang Ming, Chunfu Jia, Debin Gao
Linear Obfuscation To Combat Symbolic Execution, Zhi Wang, Jiang Ming, Chunfu Jia, Debin Gao
Research Collection School Of Computing and Information Systems
Trigger-based code (malicious in many cases, but not necessarily) only executes when specific inputs are received. Symbolic execution has been one of the most powerful techniques in discovering such malicious code and analyzing the trigger condition. We propose a novel automatic malware obfuscation technique to make analysis based on symbolic execution difficult. Unlike previously proposed techniques, the obfuscated code from our tool does not use any cryptographic operations and makes use of only linear operations which symbolic execution is believed to be good in analyzing. The obfuscated code incorporates unsolved conjectures and adds a simple loop to the original code, …
Spectral Geometry Image: Image Based 3d Models For Digital Broadcasting Applications, Boon Seng Chew, Lap Pui Chau, Ying He, Dayong Wang, Steven C. H. Hoi
Spectral Geometry Image: Image Based 3d Models For Digital Broadcasting Applications, Boon Seng Chew, Lap Pui Chau, Ying He, Dayong Wang, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
The use of 3D models for progressive transmission and broadcasting applications is an interesting challenge due to the nature and complexity of such content. In this paper, a new image format for the representation of 3D progressive model is proposed. The powerful spectral analysis is combined with the state of art Geometry Image(GI) to encode static 3D models into spectral geometry images(SGI) for robust 3D shape representation. Based on the 3D model's surface characteristics, SGI separated the geometrical image into low and high frequency layers to achieve effective Level of Details(LOD) modeling. For SGI, the connectivity data of the model …
Effective Communication Of Software Development Knowledge Through Community Portals, Christoph Treude, Margaret-Anne Storey
Effective Communication Of Software Development Knowledge Through Community Portals, Christoph Treude, Margaret-Anne Storey
Research Collection School Of Computing and Information Systems
Knowledge management plays an important role in many software organizations. Knowledge can be captured and distributed using a variety of media, including traditional help files and manuals, videos, technical articles, wikis, and blogs. In recent years, web-based community portals have emerged as an important mechanism for combining various communication channels. However, there is little advice on how they can be effectively deployed in a software project.In this paper, we present a first study of a community portal used by a closed source software project. Using grounded theory, we develop a model that characterizes documentation artifacts along several dimensions, such as …
Mining Top-K Large Structural Patterns In A Massive Network, Feida Zhu, Qiang Qu, David Lo, Xifeng Yan, Jiawei Han, Philip S. Yu
Mining Top-K Large Structural Patterns In A Massive Network, Feida Zhu, Qiang Qu, David Lo, Xifeng Yan, Jiawei Han, Philip S. Yu
Research Collection School Of Computing and Information Systems
With ever-growing popularity of social networks, web and bio-networks, mining large frequent patterns from a single huge network has become increasingly important. Yet the existing pattern mining methods cannot offer the efficiency desirable for large pattern discovery. We propose Spider- Mine, a novel algorithm to efficiently mine top-K largest frequent patterns from a single massive network with any user-specified probability of 1 − ϵ. Deviating from the existing edge-by-edge (i.e., incremental) pattern-growth framework, SpiderMine achieves its efficiency by unleashing the power of small patterns of a bounded diameter, which we call “spiders”. With the spider structure, our approach adopts a …
Improved Ordinary Measure And Image Entropy Theory Based Intelligent Copy Detection Method, Dengpan Ye, Longfei Ma, Lina Wang, Robert H. Deng
Improved Ordinary Measure And Image Entropy Theory Based Intelligent Copy Detection Method, Dengpan Ye, Longfei Ma, Lina Wang, Robert H. Deng
Research Collection School Of Computing and Information Systems
Nowadays, more and more multimedia websites appear in social network. It brings some security problems, such as privacy, piracy, disclosure of sensitive contents and so on. Aiming at copyright protection, the copy detection technology of multimedia contents becomes a hot topic. In our previous work, a new computer-based copyright control system used to detect the media has been proposed. Based on this system, this paper proposes an improved media feature matching measure and an entropy based copy detection method. The Levenshtein Distance was used to enhance the matching degree when using for feature matching measure in copy detection. For entropy …
Structural Complexity And Programmer Team Strategy: An Experimental Test, Narayan Ramasubbu, Chris F. Kemerer, Jeff Min Teck Hong
Structural Complexity And Programmer Team Strategy: An Experimental Test, Narayan Ramasubbu, Chris F. Kemerer, Jeff Min Teck Hong
Research Collection School Of Computing and Information Systems
This study develops and empirically tests the idea that the impact of structural complexity on perfective maintenance of object-oriented software is significantly determined by the team strategy of programmers (independent or collaborative). We analyzed two key dimensions of software structure, coupling and cohesion, with respect to the maintenance effort and the perceived ease-of-maintenance by pairs of programmers. Hypotheses based on the distributed cognition and task interdependence theoretical frameworks were tested using data collected from a controlled lab experiment employing professional programmers. The results show a significant interaction effect between coupling, cohesion, and programmer team strategy on both maintenance effort and …
Information Quality On The World Wide Web: Development Of A Framework, J. Kandari, E. Jones, Fiona Fui-Hoon Nah, R. Bishu
Information Quality On The World Wide Web: Development Of A Framework, J. Kandari, E. Jones, Fiona Fui-Hoon Nah, R. Bishu
Research Collection School Of Computing and Information Systems
Data consumers are provided with easy online access to information on the World Wide Web. However, consumers face information quality problems in their quest for information. This paper focuses on the development of an instrument to measure information quality (IQ) on the World Wide Web from a user's perspective. Based on a comprehensive review of the literature, 20 important IQ frameworks were identified. These models, though varied in their approach and application, share a number of characteristics regarding their classifications of the attributes of quality. The paper identifies common dimensions that exist across the existing IQ frameworks in the literature …
Certificateless Cryptography With Kgc Trust Level 3, Guomin Yang, Chik How Tan
Certificateless Cryptography With Kgc Trust Level 3, Guomin Yang, Chik How Tan
Research Collection School Of Computing and Information Systems
A normal certificateless cryptosystem can only achieve KGC trust level 2 according to the trust hierarchy defined by Girault. Although in the seminal paper introducing certificateless cryptography, Al-Riyami and Paterson introduced a binding technique to lift the KGC trust level of their certificateless schemes to level 3, many subsequent work on certificateless cryptography just focused on the constructions of normal certificateless schemes, and a formal study on the general applicability of the binding technique to these existing schemes is still missing. In this paper, to address the KGC trust level issue, we introduce the notion of Key Dependent Certificateless Cryptography …
Privacy Beyond Single Sensitive Attribute, Yuan Fang, Mafruz Zaman Ashrafi, See Kiong Ng
Privacy Beyond Single Sensitive Attribute, Yuan Fang, Mafruz Zaman Ashrafi, See Kiong Ng
Research Collection School Of Computing and Information Systems
Publishing individual specific microdata has serious privacy implications. The k-anonymity model has been proposed to prevent identity disclosure from microdata, and the work on ℓ-diversity and t-closeness attempt to address attribute disclosure. However, most current work only deal with publishing microdata with a single sensitive attribute (SA), whereas real life scenarios often involve microdata with multiple SAs that may be multi-valued. This paper explores the issue of attribute disclosure in such scenarios. We propose a method called CODIP (Complete Disjoint Projections) that outlines a general solution to deal with the shortcomings in a naïve approach. We also introduce two measures, …
Tamper Detection In The Epc Network Using Digital Watermarking, Shui-Hua Han, Chao-Hsien Chu, Zongwei Luo
Tamper Detection In The Epc Network Using Digital Watermarking, Shui-Hua Han, Chao-Hsien Chu, Zongwei Luo
Research Collection School Of Computing and Information Systems
One of the most relevant problems in radio frequency identification (RFID) technology is the lack of security measures in its wireless communication channel between the reader and tag. This article analyzes potential data tampering threats in the electronic product code (EPC) network and proposes solutions using fragile watermarking technologies.
Towards Ground Truthing Observations In Gray-Box Anomaly Detection, Jiang Ming, Haibin Zhang, Debin Gao
Towards Ground Truthing Observations In Gray-Box Anomaly Detection, Jiang Ming, Haibin Zhang, Debin Gao
Research Collection School Of Computing and Information Systems
Anomaly detection has been attracting interests from researchers due to its advantage of being able to detect zero-day exploits. A gray-box anomaly detector first observes benign executions of a computer program and then extracts reliable rules that govern the normal execution of the program. However, such observations from benign executions are not necessarily true evidences supporting the rules learned. For example, the observation that a file descriptor being equal to a socket descriptor should not be considered supporting a rule governing the two values to be the same. Ground truthing such observations is a difficult problem since it is not …
When Recommendation Meets Mobile: Contextual And Personalised Recommendation On The Go, Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Ying-Qing Xu, Shipeng Li
When Recommendation Meets Mobile: Contextual And Personalised Recommendation On The Go, Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Ying-Qing Xu, Shipeng Li
Research Collection School Of Computing and Information Systems
Mobile devices are becoming ubiquitous. People use their phones as a personal concierge discovering and making decisions anywhere and anytime. Understanding user intent on the go therefore becomes important for task completion on the phone. While existing efforts have predominantly focused on understanding the explicit user intent expressed by a textual or voice query, this paper presents an approach to context-aware and personalized entity recommendation which understands the implicit intent without any explicit user input on the phone. The approach, highly motivated from a large-scale mobile click-through analysis, is able to rank both the entity types and the entities within …
Defending Against Cross Site Scripting Attacks, Lwin Khin Shar, Hee Beng Kuan Tan
Defending Against Cross Site Scripting Attacks, Lwin Khin Shar, Hee Beng Kuan Tan
Research Collection School Of Computing and Information Systems
Researchers have proposed multiple solutions to cross-site scripting, but vulnerabilities continue to exist in many Web applications due to developers' lack of understanding of the problem and their unfamiliarity with current defenses' strengths and limitations.
A Generic Framework For Three-Factor Authentication: Preserving Security And Privacy In Distributed Systems, Xinyi Huang, Yang Xiang, Ashley Chonka, Jianying Zhou, Robert H. Deng
A Generic Framework For Three-Factor Authentication: Preserving Security And Privacy In Distributed Systems, Xinyi Huang, Yang Xiang, Ashley Chonka, Jianying Zhou, Robert H. Deng
Research Collection School Of Computing and Information Systems
As part of the security within distributed systems, various services and resources need protection from unauthorized use. Remote authentication is the most commonly used method to determine the identity of a remote client. This paper investigates a systematic approach for authenticating clients by three factors, namely password, smart card, and biometrics. A generic and secure framework is proposed to upgrade two-factor authentication to three-factor authentication. The conversion not only significantly improves the information assurance at low cost but also protects client privacy in distributed systems. In addition, our framework retains several practice-friendly properties of the underlying two-factor authentication, which we …
General Construction Of Chameleon All-But-One Trapdoor Functions, Shengli Liu, Junzuo Lai, Robert H. Deng
General Construction Of Chameleon All-But-One Trapdoor Functions, Shengli Liu, Junzuo Lai, Robert H. Deng
Research Collection School Of Computing and Information Systems
Lossy trapdoor functions enable black-box construction of public key encryption (PKE) schemes secure against chosen-ciphertext attack [18]. Recently, a more efficient black-box construction of public key encryption was given in [13] with the help of chameleon all-but-one trapdoor functions (ABO-TDFs). In this paper, we propose a black-box construction for transforming any ABO-TDFs into chameleon ABO-TDFs with the help of chameleon hash functions. Instantiating the proposed general black-box construction of chameleon ABO-TDFs, we obtain the first chameleon ABO-TDFs based on the Decisional Diffie-Hellman (DDH) assumption.
Cryptanalysis Of Hsiang-Shih's Authentication Scheme For Multi-Server Architecture, Kuo-Hui Yeh, Nai-Wei Lo, Yingjiu Li
Cryptanalysis Of Hsiang-Shih's Authentication Scheme For Multi-Server Architecture, Kuo-Hui Yeh, Nai-Wei Lo, Yingjiu Li
Research Collection School Of Computing and Information Systems
From user point of view, password-based remote user authentication technique is one of the most convenient and easy-to-use mechanisms to provide necessary security on system access. As the number of computer crimes in modern cyberspace has increased dramatically, the robustness of password-based authentication schemes has been investigated by industries and organizations in recent years. In this paper, a well-designed password-based authentication protocol for multi-server communication environment, introduced by Hsiang and Shih, is evaluated. Our security analysis indicates that their scheme is insecure against session key disclosure, server spoofing attack, and replay attack and behavior denial.
Automated Detection Of Likely Design Flaws In Layered Architectures, Aditya Budi, - Lucia, David Lo, Lingxiao Jiang, Shaowei Wang
Automated Detection Of Likely Design Flaws In Layered Architectures, Aditya Budi, - Lucia, David Lo, Lingxiao Jiang, Shaowei Wang
Research Collection School Of Computing and Information Systems
Layered architecture prescribes a good principle for separating concerns to make systems more maintainable. One example of such layered architectures is the separation of classes into three groups: Boundary, Control, and Entity, which are referred to as the three analysis class stereotypes in UML. Classes of different stereotypes are interacting with one another, when properly designed, the overall interaction would be maintainable, flexible, and robust. On the other hand, poor design would result in less maintainable system that is prone to errors. In many software projects, the stereotypes of classes are often missing, thus detection of design flaws becomes non-trivial. …
Mining Weakly Labeled Web Facial Images For Search-Based Face Annotation, Dayang Wang, Steven C. H. Hoi, Ying He
Mining Weakly Labeled Web Facial Images For Search-Based Face Annotation, Dayang Wang, Steven C. H. Hoi, Ying He
Research Collection School Of Computing and Information Systems
In this paper, we investigate a search-based face annotation framework by mining weakly labeled facial images that are freely available on the internet. A key component of such a search-based annotation paradigm is to build a database of facial images with accurate labels. This is however challenging since facial images on the WWW are often noisy and incomplete. To improve the label quality of raw web facial images, we propose an effective Unsupervised Label Refinement (ULR) approach for refining the labels of web facial images by exploring machine learning techniques. We develop effective optimization algorithms to solve the large-scale learning …
Trust Network Inference For Online Rating Data Using Generative Models, Freddy Tat Chua Chua, Ee Peng Lim
Trust Network Inference For Online Rating Data Using Generative Models, Freddy Tat Chua Chua, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In an online rating system, raters assign ratings to objects contributed by other users. In addition, raters can develop trust and distrust on object contributors depending on a few rating and trust related factors. Previous study has shown that ratings and trust links can influence each other but there has been a lack of a formal model to relate these factors together. In this paper, we therefore propose Trust Antecedent Factor (TAF)Model, a novel probabilistic model that generate ratings based on a number of rater’s and contributor’s factors. We demonstrate that parameters of the model can be learnt by Collapsed …
Message-Passing Algorithms For Quadratic Programming Formulations Of Map Estimation, Akshat Kumar, Shlomo Zilberstein
Message-Passing Algorithms For Quadratic Programming Formulations Of Map Estimation, Akshat Kumar, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
Computing maximum a posteriori (MAP) estimation in graphical models is an important inference problem with many applications. We present message-passing algorithms for quadratic programming (QP) formulations of MAP estimation for pairwise Markov random fields. In particular, we use the concave-convex procedure (CCCP) to obtain a locally optimal algorithm for the non-convex QP formulation. A similar technique is used to derive a globally convergent algorithm for the convex QP relaxation of MAP. We also show that a recently developed expectation-maximization (EM) algorithm for the QP formulation of MAP can be derived from the CCCP perspective. Experiments on synthetic and real-world problems …
A Hybrid Agent Architecture Integrating Desire, Intention And Reinforcement Learning, Ah-Hwee Tan, Yew-Soon Ong, Akejariyawong Tapanuj
A Hybrid Agent Architecture Integrating Desire, Intention And Reinforcement Learning, Ah-Hwee Tan, Yew-Soon Ong, Akejariyawong Tapanuj
Research Collection School Of Computing and Information Systems
This paper presents a hybrid agent architecture that integrates the behaviours of BDI agents, specifically desire and intention, with a neural network based reinforcement learner known as Temporal DifferenceFusion Architecture for Learning and COgNition (TD-FALCON). With the explicit maintenance of goals, the agent performs reinforcement learning with the awareness of its objectives instead of relying on external reinforcement signals. More importantly, the intention module equips the hybrid architecture with deliberative planning capabilities, enabling the agent to purposefully maintain an agenda of actions to perform and reducing the need of constantly sensing the environment. Through reinforcement learning, plans can also be …
Linking Entities To A Knowledge Base With Query Expansion, Swapna Gottipati, Jing Jiang
Linking Entities To A Knowledge Base With Query Expansion, Swapna Gottipati, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper we present a novel approach to entity linking based on a statistical language model-based information retrieval with query expansion. We use both local contexts and global world knowledge to expand query language models. We place a strong emphasis on named entities in the local contexts and explore a positional language model to weigh them differently based on their distances to the query. Our experiments on the TAC-KBP 2010 data show that incorporating such contextual information indeed aids in disambiguating the named entities and consistently improves the entity linking performance. Compared with the official results from KBP 2010 …
Cio Reporting Structure, Strategic Positioning, And Firm Performance, Rajiv D Banker, Nan Hu, Paul A Pavlou, Jerry Luftman
Cio Reporting Structure, Strategic Positioning, And Firm Performance, Rajiv D Banker, Nan Hu, Paul A Pavlou, Jerry Luftman
Research Collection School Of Computing and Information Systems
Almost 30 years after the introduction of the CIO position, the ideal CIO reporting structure (whether the CIO should report to the CEO or the CFO) is yet to be identified. There is an intuitive assumption among some proponents of IT that the CIO should always report to the CEO to promote the importance of IT and the CIO's clout in the firm, while some adversaries of IT call for a CIO—CFO reporting structure to keep a tab on IT spending. However, we challenge these two ad hoc prescriptions by arguing that neither CIO reporting structure is necessarily optimal, and …