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Full-Text Articles in Databases and Information Systems

Attribute-Based Secure Messaging In The Public Cloud, Zhi Yuan Poh, Hui Cui, Robert H. Deng, Yingjiu Li Feb 2017

Attribute-Based Secure Messaging In The Public Cloud, Zhi Yuan Poh, Hui Cui, Robert H. Deng, Yingjiu Li

Research Collection School Of Computing and Information Systems

Messaging systems operating within the public cloud are gaining popularity. To protect message confidentiality from the public cloud including the public messaging servers, we propose to encrypt messages in messaging systems using Attribute-Based Encryption (ABE). ABE is an one-to-many public key encryption system in which data are encrypted with access policies and only users with attributes that satisfy the access policies can decrypt the ciphertexts, and hence is considered as a promising solution for realizing expressive and fine-grained access control of encrypted data in public servers. Our proposed system, called Attribute-Based Secure Messaging System with Outsourced Decryption (ABSM-OD), has three …

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Unsupervised Visual Hashing With Semantic Assistant For Content-Based Image Retrieval, Lei Zhu, Jialie Shen, Liang Xie, Zhiyong Cheng Feb 2017

Unsupervised Visual Hashing With Semantic Assistant For Content-Based Image Retrieval, Lei Zhu, Jialie Shen, Liang Xie, Zhiyong Cheng

Research Collection School Of Computing and Information Systems

As an emerging technology to support scalable content-based image retrieval (CBIR), hashing has recently received great attention and became a very active research domain. In this study, we propose a novel unsupervised visual hashing approach called semantic-assisted visual hashing (SAVH). Distinguished from semi-supervised and supervised visual hashing, its core idea is to effectively extract the rich semantics latently embedded in auxiliary texts of images to boost the effectiveness of visual hashing without any explicit semantic labels. To achieve the target, a unified unsupervised framework is developed to learn hash codes by simultaneously preserving visual similarities of images, integrating the semantic …

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Using An Online Tutorial To Teach Rea Data Modeling In Accounting Information Systems Courses, Poh Sun Seow, Pan, Gary Feb 2017

Using An Online Tutorial To Teach Rea Data Modeling In Accounting Information Systems Courses, Poh Sun Seow, Pan, Gary

Research Collection School Of Accountancy

Online learning has been gaining widespread adoption due to its successin enhancing student-learning outcomes and improving student t academicperformance. This paper describes an online tutorial to teach resource-event-agent(REA) data modeling in an undergraduate accounting information systems course.The REA online tutorial reflects a self-study application designed to helpstudents improve their understanding of the REA data model. As such, thetutorial acts as a supplement to lectures by reinforcing the concepts andincorporating practices to assess student understanding. Instructors can accessthe REA online tutorial at http://smu.asg/rea. An independent survey by the University’sCentre for Teaching Excellence found a significant increase in students’perceived knowledge of REA …

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Concept-Based Interactive Search System, Yi-Jie Lu, Phuong Anh Nguyen, Hao Zhang, Chong-Wah Ngo Jan 2017

Concept-Based Interactive Search System, Yi-Jie Lu, Phuong Anh Nguyen, Hao Zhang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Our successful multimedia event detection system at TREC-VID 2015 showed its strength on handling complex concepts in a query. The system was based on a large number of pre-trained concept detectors for textual-to-visual relation. In this paper, we enhance the system by enabling human-in-the-loop. In order to facilitate a user to quickly find an information need, we incorporate concept screening, video reranking by highlighted concepts, relevance feedback and color sketch to refine a coarse retrieval result. The aim is to eventually come up with a system suitable for both Ad-hoc Video Search and Known-Item Search. In addition, as the increasing …

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Cross-Modal Recipe Retrieval: How To Cook This Dish?, Jingjing Chen, Lei Pang, Chong-Wah Ngo Jan 2017

Cross-Modal Recipe Retrieval: How To Cook This Dish?, Jingjing Chen, Lei Pang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

In social media users like to share food pictures. One intelligent feature, potentially attractive to amateur chefs, is the recommendation of recipe along with food. Having this feature, unfortunately, is still technically challenging. First, the current technology in food recognition can only scale up to few hundreds of categories, which are yet to be practical for recognizing ten of thousands of food categories. Second, even one food category can have variants of recipes that differ in ingredient composition. Finding the best-match recipe requires knowledge of ingredients, which is a fine-grained recognition problem. In this paper, we consider the problem from …

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Viewed By Too Many Or Viewed Too Little: Using Information Dissemination For Audience Segmentation, Bernard J. Jansen, Soon-Gyu Jung, Joni Salminen, Jisun An, Haewoon Kwak Jan 2017

Viewed By Too Many Or Viewed Too Little: Using Information Dissemination For Audience Segmentation, Bernard J. Jansen, Soon-Gyu Jung, Joni Salminen, Jisun An, Haewoon Kwak

Research Collection School Of Computing and Information Systems

The identification of meaningful audience segments, such as groups of users, consumers, readers, audience, etc., has important applicability in a variety of domains, including for content publishing. In this research, we seek to develop a technique for determining both information dissemination and information discrimination of online content in order to isolate audience segments. The benefits of the technique include identification of the most impactful content for analysis. With 4,320 online videos from a major news organization, a set of audience attributes, and more than 58 million interactions from hundreds of thousands of users, we isolate the key pieces of content …

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Discovering Historic Traffic-Tolerant Paths In Road Networks, Pui Hang Li, Man Lung Yiu, Kyriakos Mouratidis Jan 2017

Discovering Historic Traffic-Tolerant Paths In Road Networks, Pui Hang Li, Man Lung Yiu, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Historic traffic information is valuable in transportation analysis and planning, e.g., evaluating the reliability of routes for representative source-destination pairs. Also, it can be utilized to provide efficient and effective route-search services. In view of these applications, we propose the k traffic-tolerant paths (TTP) problem on road networks, which takes a source-destination pair and historic traffic information as input, and returns k paths that minimize the aggregate (historic) travel time. Unlike the shortest path problem, the TTP problem has a combinatorial search space that renders the optimal solution expensive to find. First, we propose an exact algorithm with effective pruning …

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Easing Cross-Border Communication: Mobile-Mediated Communication And Its Framework, Kyungsub Choi, Young Soo Kim Jan 2017

Easing Cross-Border Communication: Mobile-Mediated Communication And Its Framework, Kyungsub Choi, Young Soo Kim

Research Collection School Of Computing and Information Systems

Communication is probably the most critical component of an organization engaged in a cross-border collaboration. Today’s smart devices substantially contribute to such communication. Combined with social media, mobile communication technologies are becoming the main platform for many core functions within organizations. In this paper, we identified seven media identifiable attributes: synchronicity (SYN), de-individuation and co-presence (DCP), accessibility readiness (ARD), cognizance of environment change (CEC), wearability-portability (WRB) modality-select (MDS) and visibility (VSB). These seven attributes significantly impact the course of mobile-mediated communication. We believe that development of a theoretical perspective that embraces the complexity of mobile-mediated communication is due in order …

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Exploring Representativeness And Informativeness For Active Learning, Bo Du, Zengmao Wang, Lefei Zhang, Liangpei Zhang, Wei Liu, Jialie Shen, Dacheng Tao Jan 2017

Exploring Representativeness And Informativeness For Active Learning, Bo Du, Zengmao Wang, Lefei Zhang, Liangpei Zhang, Wei Liu, Jialie Shen, Dacheng Tao

Research Collection School Of Computing and Information Systems

How can we find a general way to choose the most suitable samples for training a classifier? Even with very limited prior information? Active learning, which can be regarded as an iterative optimization procedure, plays a key role to construct a refined training set to improve the classification performance in a variety of applications, such as text analysis, image recognition, social network modeling, etc. Although combining representativeness and informativeness of samples has been proven promising for active sampling, state-of-the-art methods perform well under certain data structures. Then can we find a way to fuse the two active sampling criteria without …

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High Impact Bug Report Identification With Imbalanced Learning Strategies, Xinli Yang, David Lo, Xin Xia, Qiao Huang, Jianling Sun Jan 2017

High Impact Bug Report Identification With Imbalanced Learning Strategies, Xinli Yang, David Lo, Xin Xia, Qiao Huang, Jianling Sun

Research Collection School Of Computing and Information Systems

In practice, some bugs have more impact than others and thus deserve more immediate attention. Due to tight schedule and limited human resources, developers may not have enough time to inspect all bugs. Thus, they often concentrate on bugs that are highly impactful. In the literature, high-impact bugs are used to refer to the bugs which appear at unexpected time or locations and bring more unexpected effects (i.e., surprise bugs), or break pre-existing functionalities and destroy the user experience (i.e., breakage bugs). Unfortunately, identifying high-impact bugs from thousands of bug reports in a bug tracking system is not an easy …

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Safestack+: Enhanced Dual Stack To Combat Data-Flow Hijacking, Yan Lin, Xiaoxiao Tang, Debin Gao Jan 2017

Safestack+: Enhanced Dual Stack To Combat Data-Flow Hijacking, Yan Lin, Xiaoxiao Tang, Debin Gao

Research Collection School Of Computing and Information Systems

SafeStack, initially proposed as a key component of Code Pointer Integrity (CPI), separates the program stack into two distinct regions to provide a safe region for sensitive code pointers. SafeStack can prevent buffer overflow attacks that overwrite sensitive code pointers, e.g., return addresses, to hijack control flow of the program, and has been incorporated into the Clang project of LLVM as a C-based language front-end. In this paper, we propose and implement SafeStack+, an enhanced dual stack LLVM plug-in that further protects programs from data-flow hijacking. SafeStack+ locates data flow sensitive variables on the unsafe stack that could potentially affect …

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Internet Health Information Seeking And The Patient-Physician Relationship: A Systematic Review, Sharon Swee-Lin Tan, Nadee Goonawardene Jan 2017

Internet Health Information Seeking And The Patient-Physician Relationship: A Systematic Review, Sharon Swee-Lin Tan, Nadee Goonawardene

Research Collection School Of Computing and Information Systems

Background: With online health information becoming increasingly popular among patients, concerns have been raised about the impact of patients' Internet health information-seeking behavior on their relationship with physicians. Therefore, it is pertinent to understand the influence of online health information on the patient-physician relationship. Objective: Our objective was to systematically review existing research on patients' Internet health information seeking and its influence on the patient-physician relationship. Methods: We systematically searched PubMed and key medical informatics, information systems, and communication science journals covering the period of 2000 to 2015. Empirical articles that were in English were included. We analyzed the content …

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Using An Online Learning Tutorial To Teach Rea Data Modelling In Accounting Information Systems Courses, Poh Sun Seow, Gary Pan Jan 2017

Using An Online Learning Tutorial To Teach Rea Data Modelling In Accounting Information Systems Courses, Poh Sun Seow, Gary Pan

Research Collection School Of Accountancy

Online learning has been gaining widespread adoption due to its success in enhancing student-learning outcomes and improving student academic performance. This paper describes an online tutorial to teach resource-event-agent (REA) data modeling in an undergraduate accounting information systems course. The REA online tutorial reflects a self-study application designed to help students improve their understanding of the REA data model. As such, the tutorial acts as a supplement to lectures by reinforcing the concepts and incorporating practices to assess student understanding. Instructors can access the REA online tutorial at http://smu.sg/rea. An independent survey by the University's Centre for Teaching Excellence found …

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Collaboration In Virtual Worlds: Impact Of Task Complexity On Team Trust And Satisfaction, Fiona Fui-Hoon Nah, Shu Schiller, Brian E. Mennecke, Keng Siau Jan 2017

Collaboration In Virtual Worlds: Impact Of Task Complexity On Team Trust And Satisfaction, Fiona Fui-Hoon Nah, Shu Schiller, Brian E. Mennecke, Keng Siau

Research Collection School Of Computing and Information Systems

Virtual worlds are three-dimensional, computer-generated worlds in which team collaboration can be facilitated through the use of shared virtual space and mediated using avatars. This article examines the effect of task complexity on team collaboration. A puzzle game in Second Life was used as the collaborative task and task complexity was manipulated by varying the number of pieces in the puzzle. The hypotheses are that task complexity influences team trust, and team trust influences team process satisfaction in virtual team collaboration. The experimental results indicate that task complexity has significant effects on team trust and team process satisfaction, and team …

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Validating Social Media Data For Automatic Persona Generation, Jisun An, Haewoon Kwak, Bernard J Jansen Dec 2016

Validating Social Media Data For Automatic Persona Generation, Jisun An, Haewoon Kwak, Bernard J Jansen

Research Collection School Of Computing and Information Systems

Using personas during interactive design has considerable potential for product and content development. Unfortunately, personas have typically been a fairly static technique. In this research, we validate an approach for creating personas in real time, based on analysis of actual social media data in an effort to automate the generation of personas. We validate that social media data can be implemented as an approach for automating generating personas in real time using actual YouTube social media data from a global media corporation that produces online digital content. Using the organization's YouTube channel, we collect demographic data, customer interactions, and topical …

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Designing A Datawarehousing And Business Analytics Course Using Experiential Learning Pedagogy, Gottipati Swapna, Venky Shankararaman Dec 2016

Designing A Datawarehousing And Business Analytics Course Using Experiential Learning Pedagogy, Gottipati Swapna, Venky Shankararaman

Research Collection School Of Computing and Information Systems

Experiential learning refers to learning from experience or learning by doing. Universities have explored various forms for implementing experiential learning such as apprenticeships, internships, cooperative education, practicums, service learning, job shadowing, fellowships and community activities. However, very little has been done in systematically trying to integrate experiential learning to the main stream academic curriculum. Over the last two years, at the authors’ university, a new program titled UNI-X was launched to achieve this. Combining academic curriculum with experiential learning pedagogy, provides a challenging environment for students to use their disciplinary knowledge and skills to tackle real world problems and issues …

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Zero++: Harnessing The Power Of Zero Appearances To Detect Anomalies In Large-Scale Data Sets, Guansong Pang, Kai Ming Ting, David Albrecht, Huidong Jin Dec 2016

Zero++: Harnessing The Power Of Zero Appearances To Detect Anomalies In Large-Scale Data Sets, Guansong Pang, Kai Ming Ting, David Albrecht, Huidong Jin

Research Collection School Of Computing and Information Systems

This paper introduces a new unsupervised anomaly detector called ZERO++ which employs the number of zero appearances in subspaces to detect anomalies in categorical data. It is unique in that it works in regions of subspaces that are not occupied by data; whereas existing methods work in regions occupied by data. ZERO++ examines only a small number of low dimensional subspaces to successfully identify anomalies. Unlike existing frequencybased algorithms, ZERO++ does not involve subspace pattern searching. We show that ZERO++ is better than or comparable with the state-of-the-art anomaly detection methods over a wide range of real-world categorical and numeric …

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Unsupervised Feature Selection For Outlier Detection By Modelling Hierarchical Value-Feature Couplings, Guansong Pang, Longbing Cao, Ling Chen, Huan Liu Dec 2016

Unsupervised Feature Selection For Outlier Detection By Modelling Hierarchical Value-Feature Couplings, Guansong Pang, Longbing Cao, Ling Chen, Huan Liu

Research Collection School Of Computing and Information Systems

Proper feature selection for unsupervised outlier detection can improve detection performance but is very challenging due to complex feature interactions, the mixture of relevant features with noisy/redundant features in imbalanced data, and the unavailability of class labels. Little work has been done on this challenge. This paper proposes a novel Coupled Unsupervised Feature Selection framework (CUFS for short) to filter out noisy or redundant features for subsequent outlier detection in categorical data. CUFS quantifies the outlierness (or relevance) of features by learning and integrating both the feature value couplings and feature couplings. Such value-to-feature couplings capture intrinsic data characteristics and …

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Cryptographic Reverse Firewall Via Malleable Smooth Projective Hash Functions, Rongmao Chen, Guomin Yang, Guomin Yang, Willy Susilo, Fuchun Guo, Mingwu Zhang Dec 2016

Cryptographic Reverse Firewall Via Malleable Smooth Projective Hash Functions, Rongmao Chen, Guomin Yang, Guomin Yang, Willy Susilo, Fuchun Guo, Mingwu Zhang

Research Collection School Of Computing and Information Systems

Motivated by the revelations of Edward Snowden, postSnowden cryptography has become a prominent research direction in recent years. In Eurocrypt 2015, Mironov and Stephens-Davidowitz proposed a novel concept named cryptographic reverse firewall (CRF) which can resist exfiltration of secret information from an arbitrarily compromised machine. In this work, we continue this line of research and present generic CRF constructions for several widely used cryptographic protocols based on a new notion named malleable smooth projective hash function. Our contributions can be summarized as follows. – We introduce the notion of malleable smooth projective hash function, which is an extension of the …

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Iterated Random Oracle: A Universal Approach For Finding Loss In Security Reduction, Fuchun Guo, Willy Susilo, Yi Mu, Rongmao Chen, Jianchang Lai, Guomin Yang Dec 2016

Iterated Random Oracle: A Universal Approach For Finding Loss In Security Reduction, Fuchun Guo, Willy Susilo, Yi Mu, Rongmao Chen, Jianchang Lai, Guomin Yang

Research Collection School Of Computing and Information Systems

The indistinguishability security of a public-key cryptosystem can be reduced to a computational hard assumption in the random oracle model, where the solution to a computational hard problem is hidden in one of the adversary’s queries to the random oracle. Usually, there is a finding loss in finding the correct solution from the query set, especially when the decisional variant of the computational problem is also hard. The problem of finding loss must be addressed towards tight(er) reductions under this type. In EUROCRYPT 2008, Cash, Kiltz and Shoup proposed a novel approach using a trapdoor test that can solve the …

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Pairwise Relation Classification With Mirror Instances And A Combined Convolutional Neural Network, Jianfei Yu, Jing Jiang Dec 2016

Pairwise Relation Classification With Mirror Instances And A Combined Convolutional Neural Network, Jianfei Yu, Jing Jiang

Research Collection School Of Computing and Information Systems

Relation classification is the task of classifying the semantic relations between entity pairs in text. Observing that existing work has not fully explored using different representations for relation instances, especially in order to better handle the asymmetry of relation types, in this paper, we propose a neural network based method for relation classification that combines the raw sequence and the shortest dependency path representations of relation instances and uses mirror instances to perform pairwise relation classification. We evaluate our proposed models on two widely used datasets: SemEval-2010 Task 8 and ACE-2005. The empirical results show that our combined model together …

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Efficient Online Summarization Of Large-Scale Dynamic Networks, Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen Dec 2016

Efficient Online Summarization Of Large-Scale Dynamic Networks, Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen

Research Collection School Of Computing and Information Systems

Information diffusion in social networks is often characterized by huge participating communities and viral cascades of high dynamicity. To observe, summarize, and understand the evolution of dynamic diffusion processes in an informative and insightful way is a challenge of high practical value. However, few existing studies aim to summarize networks for interesting dynamic patterns. Dynamic networks raise new challenges not found in static settings, including time sensitivity, online interestingness evaluation, and summary traceability, which render existing techniques inadequate. We propose dynamic network summarization to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or …

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From Footprint To Evidence: An Exploratory Study Of Mining Social Data For Credit Scoring, Guangming Guo, Feida Zhu, Enhong Chen, Qi Liu, Le Wu, Chu Guan Dec 2016

From Footprint To Evidence: An Exploratory Study Of Mining Social Data For Credit Scoring, Guangming Guo, Feida Zhu, Enhong Chen, Qi Liu, Le Wu, Chu Guan

Research Collection School Of Computing and Information Systems

With the booming popularity of online social networks like Twitter and Weibo, online user footprints are accumulating rapidly on the social web. Simultaneously, the question of how to leverage the large-scale user-generated social media data for personal credit scoring comes into the sight of both researchers and practitioners. It has also become a topic of great importance and growing interest in the P2P lending industry. However, compared with traditional financial data, heterogeneous social data presents both opportunities and challenges for personal credit scoring. In this article, we seek a deep understanding of how to learn users’ credit labels from social …

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Cast2face: Assigning Character Names Onto Faces In Movie With Actor-Character Correspondence, Guangyu Gao, Mengdi Xu, Jialie Shen, Huangdong Ma, Shuicheng Yan Dec 2016

Cast2face: Assigning Character Names Onto Faces In Movie With Actor-Character Correspondence, Guangyu Gao, Mengdi Xu, Jialie Shen, Huangdong Ma, Shuicheng Yan

Research Collection School Of Computing and Information Systems

Automatically identifying characters in movies has attracted researchers' interest and led to several significant and interesting applications. However, due to the vast variation in character appearance as well as the weakness and ambiguity of available annotation, it is still a challenging problem. In this paper, we investigate this problem with the supervision of actor-character name correspondence provided by the movie cast. Our proposed framework, namely, Cast2Face, is featured by: 1) we restrict the assigned names within the set of character names in the cast; 2) for each character, by using the corresponding actor and movie name as keywords, we retrieve …

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Careermapper: An Automated Resume Evaluation Tool, Vivian Lai, Kyong Jin Shim, Richard J. Oentaryo, Philips K. Prasetyo, Casey Vu, Ee-Peng Lim, David Lo Dec 2016

Careermapper: An Automated Resume Evaluation Tool, Vivian Lai, Kyong Jin Shim, Richard J. Oentaryo, Philips K. Prasetyo, Casey Vu, Ee-Peng Lim, David Lo

Research Collection School Of Computing and Information Systems

The advent of the Web brought about major changes in the way people search for jobs and companies look for suitable candidates. As more employers and recruitment firms turn to the Web for job candidate search, an increasing number of people turn to the Web for uploading and creating their online resumes. Resumes are often the first source of information about candidates and also the first item of evaluation in candidate selection. Thus, it is imperative that resumes are complete, free of errors and well-organized. We present an automated resume evaluation tool called 'CareerMapper'. Our tool is designed to conduct …

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Answering Why-Not And Why Questions On Reverse Top-K Queries, Qing Liu, Yunjun Gao, Gang Chen, Baihua Zheng, Linlin Zhou Dec 2016

Answering Why-Not And Why Questions On Reverse Top-K Queries, Qing Liu, Yunjun Gao, Gang Chen, Baihua Zheng, Linlin Zhou

Research Collection School Of Computing and Information Systems

Why-not and why questions can be posed by database users to seek clarifications on unexpected query results. Specifically, why-not questions aim to explain why certain expected tuples are absent from the query results, while why questions try to clarify why certain unexpected tuples are present in the query results. This paper systematically explores the why-not and why questions on reverse top-k queries, owing to its importance in multi-criteria decision making. We first formalize why-not questions on reverse top-k queries, which try to include the missing objects in the reverse top-k query results, and then, we propose a unified framework called …

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Impact Of Isp, Bpr, And Customization On Erp Performance In Manufacturing Smes Of Korea, Soon-Goo Hong, Keng Siau, Jong-Weon Kim Dec 2016

Impact Of Isp, Bpr, And Customization On Erp Performance In Manufacturing Smes Of Korea, Soon-Goo Hong, Keng Siau, Jong-Weon Kim

Research Collection School Of Computing and Information Systems

Purpose: This paper aims to assess how enterprise resource planning (ERP) performance of Korean small and medium enterprises in manufacturing differs according to different levels of business process reengineering (BPR), information strategic planning (ISP) and ERP customization. Design/methodology/approach: A questionnaire survey was carried out in this research. Responses from 96 small and medium manufacturing companies that have adopted ERP systems were analyzed. Findings: The results of this study suggest that ISP and BPR implementation are positively correlated to ERP performance. Originality/value: While consulting and customization costs have positive impacts on ERP performance, the level of customization does not influence performance. …

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Coherence, Richness And Cognitive Absorption In Website Design, L. Visinescu, Fiona Fui-Hoon Nah Dec 2016

Coherence, Richness And Cognitive Absorption In Website Design, L. Visinescu, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Kaplan’s theory on environmental preferences can offer a holistic perspective on cognitive absorption in ecommerce website design. Drawing on Kaplan’s theory, this paper proposes that coherence and richness of a website can enhance cognitive absorption of users. The findings from our study not only support the hypotheses, but also suggest that coherence and richness can reach an optimal proportion in website design, after which they are inversely correlated.

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Data Exfiltration Detection And Prevention: Virtually Distributed Pomdps For Practically Safer Networks, Sara Marie Mc Carthy, Arunesh Sinha, Milind Tambe, Pratyusa Manadhata Nov 2016

Data Exfiltration Detection And Prevention: Virtually Distributed Pomdps For Practically Safer Networks, Sara Marie Mc Carthy, Arunesh Sinha, Milind Tambe, Pratyusa Manadhata

Research Collection School Of Computing and Information Systems

We address the challenge of detecting and addressing advanced persistent threats (APTs) in a computer network, focusing in particular on the challenge of detecting data exfiltration over Domain Name System (DNS) queries, where existing detection sensors are imperfect and lead to noisy observations about the network’s security state. Data exfiltration over DNS queries involves unauthorized transfer of sensitive data from an organization to a remote adversary through a DNS data tunnel to a malicious web domain. Given the noisy sensors, previous work has illustrated that standard approaches fail to satisfactorily rise to the challenge of detecting exfiltration attempts. Instead, we …

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Aspect-Based Helpfulness Prediction For Online Product Reviews, Yinfei Yang, Cen Chen, Forrest Sheng Bao Nov 2016

Aspect-Based Helpfulness Prediction For Online Product Reviews, Yinfei Yang, Cen Chen, Forrest Sheng Bao

Research Collection School Of Computing and Information Systems

Product reviews greatly influence purchase decisions in online shopping. A common burden of online shopping is that consumers have to search for the right answers through massive reviews, especially on popular products. Hence, estimating and predicting the helpfulness of reviews become important tasks to directly improve shopping experience. In this paper, we propose a new approach to helpfulness prediction by leveraging aspect analysis of reviews. Our hypothesis is that a helpful review will cover many aspects of a product at different emphasis levels. The first step to tackle this problem is to extract proper aspects. Because related products share common …

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