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Full-Text Articles in Entire DC Network
Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng
Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng
Research Collection School Of Computing and Information Systems
Social networking has grown rapidly over the last few years, and social networks contain a huge amount of content. However, it can be not easy to navigate the social networks to find specific information. In this paper, we define a new type of queries, namely context-aware nearest neighbor (CANN) search over social network to retrieve the nearest node to the query node that matches the context specified. CANN considers both the structure of the social network, and the profile information of the nodes. We design ahyper-graph based index structure to support approximated CANN search efficiently.
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.
On Modeling Virality Of Twitter Content, Tuan Anh Hoang, Ee Peng Lim, Palakorn Achananuparp, Jing Jiang, Feida Zhu
On Modeling Virality Of Twitter Content, Tuan Anh Hoang, Ee Peng Lim, Palakorn Achananuparp, Jing Jiang, Feida Zhu
Research Collection School Of Computing and Information Systems
Twitter is a popular microblogging site where users can easily use mobile phones or desktop machines to generate short messages to be shared with others in realtime. Twitter has seen heavy usage in many recent international events including Japan earthquake, Iran election, etc. In such events, many tweets may become viral for different reasons. In this paper, we study the virality of socio-political tweet content in the Singapore’s 2011 general election (GE2011). We collected tweet data generated by about 20K Singapore users from 1 April 2011 till 12 May 2011, and the follow relationships among them. We introduce several quantitative …
Towards A Model Checker For Nesc And Wireless Sensor Networks, Manchun Zheng, Jun Sun, Yang Liu, Jin Song Dong, Yu Gu
Towards A Model Checker For Nesc And Wireless Sensor Networks, Manchun Zheng, Jun Sun, Yang Liu, Jin Song Dong, Yu Gu
Research Collection School Of Computing and Information Systems
Wireless sensor networks (WSNs) are expected to run unattendedly for critical tasks. To guarantee the correctness of WSNs is important, but highly nontrivial due to the distributed nature. In this work, we present an automatic approach to directly verify WSNs built with TinyOS applications implemented in the NesC language. To achieve this target, we firstly define a set of formal operational semantics for most of the NesC language structures for the first time. This allows us to capture the behaviors of sensors by labelled transition systems (LTSs), which are the underlying semantic models of NesC programs. Secondly, WSNs are modeled …
Allocating Resources In Multiagent Flowshops With Adaptive Auctions, Hoong Chuin Lau, Zhengyi Zhao, Sam Shuzhi Ge, Thong Heng Lee
Allocating Resources In Multiagent Flowshops With Adaptive Auctions, Hoong Chuin Lau, Zhengyi Zhao, Sam Shuzhi Ge, Thong Heng Lee
Research Collection School Of Computing and Information Systems
In this paper, we consider the problem of allocating machine resources among multiple agents, each of which is responsible to solve a flowshop scheduling problem. We present an iterated combinatorial auction mechanism in which bid generation is performed within each agent, while a price adjustment procedure is performed by a centralized auctioneer. While this approach is fairly well-studied in the literature, our primary innovation is in an adaptive price adjustment procedure, utilizing variable step-size inspired by adaptive PID-control theory coupled with utility pricing inspired by classical microeconomics. We compare with the conventional price adjustment scheme proposed in Fisher (1985), and …
Location-Dependent Spatial Query Containment, Ken C. K. Lee, Brandon Unger, Baihua Zheng, Wang-Chien Lee
Location-Dependent Spatial Query Containment, Ken C. K. Lee, Brandon Unger, Baihua Zheng, Wang-Chien Lee
Research Collection School Of Computing and Information Systems
Nowadays, location-related information is highly accessible to mobile users via issuing Location-Dependent Spatial Queries (LDSQs) with respect to their locations wirelessly to Location-Based Service (LBS) servers. Due to the limited mobile device battery energy, scarce wireless bandwidth, and heavy LBS server workload, the number of LDSQs submitted over wireless channels to LBS servers for evaluation should be minimized as appropriate. In this paper, we exploit query containment techniques for LDSQs (called LDSQ containment) to enable mobile clients to determine whether the result of a new LDSQ Q′ is completely covered by that of another LDSQ Q previously answered by a …
Using Social Annotations For Trend Discovery In Scientific Publications, Meiqun Hu, Ee Peng Lim, Jing Jiang
Using Social Annotations For Trend Discovery In Scientific Publications, Meiqun Hu, Ee Peng Lim, Jing Jiang
Research Collection School Of Computing and Information Systems
Social tags and citing documents are two forms of social annotations to scientific publications. These social annotations provide useful contextual and temporal information for the annotated work, which encapsulates the attention and interest of the annotators. In this work, we explore the use of social annotations for discovering trends in scientific publications. We propose a trend discovery process that employs trend estimation and trend selection and ranking for analyzing the emerging trends shown in the social annotation profiles. The proposed sigmoid trend estimator allows us to characterize and compare how much, when and how fast the trends emerge. To perform …
Active Multiple Kernel Learning For Interactive 3d Object Retrieval Systems, Steven C. H. Hoi, Rong Jin
Active Multiple Kernel Learning For Interactive 3d Object Retrieval Systems, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
An effective relevance feedback solution plays a key role in interactive intelligent 3D object retrieval systems. In this work, we investigate the relevance feedback problem for interactive intelligent 3D object retrieval, with the focus on studying effective machine learning algorithms for improving the user's interaction in the retrieval task. One of the key challenges is to learn appropriate kernel similarity measure between 3D objects through the relevance feedback interaction with users. We address this challenge by presenting a novel framework of Active multiple kernel learning (AMKL), which exploits multiple kernel learning techniques for relevance feedback in interactive 3D object retrieval. …
Direction-Based Surrounder Queries For Mobile Recommendations, Xi Guo, Baihua Zheng, Yoshiharu Ishikawa, Yunjun Gao
Direction-Based Surrounder Queries For Mobile Recommendations, Xi Guo, Baihua Zheng, Yoshiharu Ishikawa, Yunjun Gao
Research Collection School Of Computing and Information Systems
Location-based recommendation services recommend objects to the user based on the user’s preferences. In general, the nearest objects are good choices considering their spatial proximity to the user. However, not only the distance of an object to the user but also their directional relationship are important. Motivated by these, we propose a new spatial query, namely a direction-based surrounder (DBS) query, which retrieves the nearest objects around the user from different directions. We define the DBS query not only in a two-dimensional Euclidean space E">EE but also in a road network R">RR . In the Euclidean space E" …
Adaptive Collision Resolution For Efficient Rfid Tag Identification, Yung-Chun Chen, Kuo-Hui Yeh, Nai-Wei Lo, Yingjiu Li, Enrico Winata
Adaptive Collision Resolution For Efficient Rfid Tag Identification, Yung-Chun Chen, Kuo-Hui Yeh, Nai-Wei Lo, Yingjiu Li, Enrico Winata
Research Collection School Of Computing and Information Systems
In large-scale RFID systems, all of the communications between readers and tags are via a shared wireless channel. When a reader intends to collect all IDs from numerous existing tags, a tag identification process is invoked by the reader to collect the tags' IDs. This phenomenon results in tag-to-reader signal collisions which may suppress the system performance greatly. To solve this problem, we design an efficient tag identification protocol in which a significant gain is obtained in terms of both identification delay and communication overhead. A k-ary tree-based abstract is adopted in our proposed tag identification protocol as underlying architecture …
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 …
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 …
An Exploratory Study Of Software Reverse Engineering In A Security Context, Christoph Treude, Fernando Figueira Filho, Margaret-Anne Storey, Martin Salois
An Exploratory Study Of Software Reverse Engineering In A Security Context, Christoph Treude, Fernando Figueira Filho, Margaret-Anne Storey, Martin Salois
Research Collection School Of Computing and Information Systems
Illegal cyberspace activities are increasing rapidly and many software engineers are using reverse engineering methods to respond to attacks. The security-sensitive nature of these tasks, such as the understanding of malware or the decryption of encrypted content, brings unique challenges to reverse engineering: work has to be done offline, files can rarely be shared, time pressure is immense, and there is a lack of tool and process support for capturing and sharing the knowledge obtained while trying to understand plain assembly code. To help us gain an understanding of this reverse engineering work, we report on an exploratory study done …
Active Multiple Kernel Learning For Interactive 3d Object Retrieval Systems, Steven C. H. Hoi, Rong Jin
Active Multiple Kernel Learning For Interactive 3d Object Retrieval Systems, Steven C. H. Hoi, Rong Jin
Research Collection School Of Computing and Information Systems
An effective relevance feedback solution plays a key role in interactive intelligent 3D object retrieval systems. In this work, we investigate the relevance feedback problem for interactive intelligent 3D object retrieval, with the focus on studying effective machine learning algorithms for improving the user's interaction in the retrieval task. One of the key challenges is to learn appropriate kernel similarity measure between 3D objects through the relevance feedback interaction with users. We address this challenge by presenting a novel framework of Active multiple kernel learning (AMKL), which exploits multiple kernel learning techniques for relevance feedback in interactive 3D object retrieval. …
Packed, Printable, And Polymorphic Return-Oriented Programming, Kangjie Lu, Dabi Zou, Weiping Wen, Debin Gao
Packed, Printable, And Polymorphic Return-Oriented Programming, Kangjie Lu, Dabi Zou, Weiping Wen, Debin Gao
Research Collection School Of Computing and Information Systems
Return-oriented programming (ROP) is an attack that has been shown to be able to circumvent W ⊕ X protection. However, it was not clear if ROP can be made as powerful as non-ROP malicious code in other aspects, e.g., be packed to make static analysis difficult, be printable to evade non-ASCII filtering, be polymorphic to evade signature-based detection, etc. Research in these potential advances in ROP is important in designing counter-measures. In this paper, we show that ROP code could be packed, printable, and polymorphic. We demonstrate this by proposing a packer that produces printable and polymorphic ROP code. It …
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, …
Enhancing Brand Equity Through Flow And Telepresence: A Comparison Of 2d And 3d Virtual Worlds, Fiona Fui-Hoon Nah, B. Eschenbrenner, D. Dewester
Enhancing Brand Equity Through Flow And Telepresence: A Comparison Of 2d And 3d Virtual Worlds, Fiona Fui-Hoon Nah, B. Eschenbrenner, D. Dewester
Research Collection School Of Computing and Information Systems
This research uses theories of flow, telepresence, positive emotions, and brand equity to examine the effect of using two-dimensional versus three-dimensional virtual world environments on telepresence, enjoyment, brand equity, and behavioral intention. The findings suggest that the 3D virtual world environment produces both positive and negative effects on brand equity when compared to the 2D environment. The positive effect of the 3D virtual world environment on brand equity occurs through telepresence, a specific aspect of flow, as well as enjoyment. The negative effect on brand equity can be explained using distraction-conflict theory in which attentional conflicts faced by users of …
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 …
An Efficient Adaptive Vortex Particle Method For Real-Time Smoke Simulation, Shengfeng He, Hon-Cheng Wong, Un-Hong Wong
An Efficient Adaptive Vortex Particle Method For Real-Time Smoke Simulation, Shengfeng He, Hon-Cheng Wong, Un-Hong Wong
Research Collection School Of Computing and Information Systems
Smoke simulation is one of the interesting topics in computer animation and it usually involves turbulence generation. Efficient generation of realistic turbulent flows becomes one of the challenges in smoke simulation. Vortex particle method, which is a hybrid method that combines grid-based and particle-based approaches, is often used for generating turbulent details. However, it may cause irrational artifacts due to its initial condition and vorticity forcing approach used. In this paper, a new vorticity forcing approach based on the spatial adaptive vorticity confinement is proposed to address this problem. In this approach, the spatial adaptive vorticity confinement force varies with …
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 …
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 …
On Detection Of Erratic Arguments, Jin Han, Qiang Yan, Robert H. Deng, Debin Gao
On Detection Of Erratic Arguments, Jin Han, Qiang Yan, Robert H. Deng, Debin Gao
Research Collection School Of Computing and Information Systems
Due to the erratic nature, the value of a function argument in one normal program execution could become illegal in another normal execution context. Attacks utilizing such erratic arguments are able to evade detections as fine-grained context information is unavailable in many existing detection schemes. In order to obtain such fine-grained context information, a precise model on the internal program states has to be built, which is impractical especially monitoring a closed source program alone. In this paper, we propose an intrusion detection scheme which builds on two diverse programs providing semantically-close functionality. Our model learns underlying semantic correlation of …
Structural Analysis Of The Hot Spots In The Binding Between H1n1 Ha And The 2di Antibody: Do Mutations Of H1n1 From 1918 To 2009 Affect Much On This Binding?, Qian Liu, Steven C. H. Hoi, Chinh T. T. Su, Zhenhua Li, Chee-Keong Kwoh, Limsoon Wong, Jinyan Li
Structural Analysis Of The Hot Spots In The Binding Between H1n1 Ha And The 2di Antibody: Do Mutations Of H1n1 From 1918 To 2009 Affect Much On This Binding?, Qian Liu, Steven C. H. Hoi, Chinh T. T. Su, Zhenhua Li, Chee-Keong Kwoh, Limsoon Wong, Jinyan Li
Research Collection School Of Computing and Information Systems
Worldwide and substantial mortality caused by the 2009 H1N1 influenza A has stimulated a new surge of research on H1N1 viruses. An epitope conservation has been learned in the HA1 protein that allows antibodies to cross-neutralize both 1918 and 2009 H1N1. However, few works have thoroughly studied the binding hot spots in those two antigen–antibody interfaces which are responsible for the antibody cross-neutralization. We apply predictive methods to identify binding hot spots at the epitope sites of the HA1 proteins and at the paratope sites of the 2D1 antibody. We find that the six mutations at the HA1's epitope from …
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 …
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 …
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 …
Driverguard: A Fine-Grained Protection On I/O Flow, Yueqiang Cheng, Xuhua Ding, Robert H. Deng
Driverguard: A Fine-Grained Protection On I/O Flow, Yueqiang Cheng, Xuhua Ding, Robert H. Deng
Research Collection School Of Computing and Information Systems
Most commodity peripheral devices and their drivers are geared to achieve high performance with security functions being opted out. The absence of security measures invites attacks on the I/O data and consequently threats those applications feeding on them, such as biometric authentication. In this paper, we present the design and implementation of DriverGuard, a hypervisor based protection mechanism which dynamically shields I/O flows such that I/O data are not exposed to the malicious kernel. Our design leverages a composite of cryptographic and virtualization techniques to achieve fine-grained protection. DriverGuard is lightweight as it only needs to protect around 2% of …
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, …