Digital Commons Network^™

Identity-Based Encryption Transformation For Flexible Sharing Of Encrypted Data In Public Cloud, Robert H. Deng, Zheng Qin, Qianhong Wu, Zhenyu Guan, Robert H. Deng, Yujue Wang, Yunya Zhou

Research Collection School Of Computing and Information Systems

With the rapid development of cloud computing, an increasing number of individuals and organizations are sharing data in the public cloud. To protect the privacy of data stored in the cloud, a data owner usually encrypts his data in such a way that certain designated data users can decrypt the data. This raises a serious problem when the encrypted data needs to be shared to more people beyond those initially designated by the data owner. To address this problem, we introduce and formalize an identity-based encryption transformation (IBET) model by seamlessly integrating two well-established encryption mechanisms, namely identity-basedencryption (IBE) and …

Energy-Efficient Distance-Bounding With Residual Charge Computation, Yunhui Zhuang, Anjia Yang, Gerhard Hancke, Duncan S. Wong, Guomin Yang

Research Collection School Of Computing and Information Systems

Real-time location systems are often required in industrial applications. In addition to securely determining an item's location, these systems also need to accommodate energy-limited tracking tokens. Distance-bounding protocols enable a Verifier to cryptographically determine an upper-bound on the physical distance to a Prover by measuring the round-trip time of specially designed challenge-response messages. This type of protocols serve as countermeasure to three common attacks on location-based systems and have been extensively studied with the goal of achieving optimal security bounds for the respective attacks. In this paper, we propose a new energy-efficient distance-bounding protocol that protects against all three common …

Techniques To Visualize Occluded Graph Elements For 2.5d Map Editing, Kazuyuki Fujita, Daigo Hayashi, Kotaro Hara, Kazuki Takashima, Yoshifumi Kitamura

Research Collection School Of Computing and Information Systems

We propose an interface with two novel techniques to visualize occluded graph nodes and edges that help the user edit map data with a 2.5D geographical structure (e.g., multi-floor indoor maps). We first design a visualization technique —Repel Signification— that employs micro-animation to signify the graph elements that are overlapping with each other (and potentially erroneous). We also design a technique that enables the user to edit the occluded components with Expansion Interaction, which simultaneously visualizes both in-floor and across-floor occluded connections between the map elements. The combination of the two methods would enable the map editors (non-experts) to effectively …

A Global Regression Method For Thermal Sharpening Of Urban Land Surface Temperatures From Modis And Landsat, James. W. Wang, Winston T. L. Chow, Yi-Chen Wang

Research Collection School of Social Sciences

Land surface temperatures (LST) in urban landscapes are typically more heterogeneous than can be monitored by the spatial resolution of satellite-based thermal infrared sensors. Thermal sharpening (TS) methods permit the disaggregation of LST based on finer-grained multispectral information, but there is continued debate over which spectral indices are most appropriate for urban TS, and how they should be configured in a predictive regression framework. In this study, we evaluate the stability of various TS kernels with respect to LST at different spatial (Landsat 8) and diurnal (MODIS) scales, and present a new TS method, global regression for urban thermal sharpening …

Free Bodies, Segmented Selves: Paradoxical Spaces Of Dancehall Culture In Singapore, Orlando Woods

Research Collection School of Social Sciences

This paper contributes to the ongoing expansion of the geographies of encounter by considering how cultural encounters can lead to the realisation, and the segmentation, of the self. As much as cultural differences can be manifested, negotiated and managed externally, so too can these differences be internal states that are realised through engagements with the embodied self. Accordingly, segmented selves are an outcome of the desire for individuals to compartmentalise diverse and disaggregated lives, and to retain a sense of cohesion and harmony within the various socio-cultural communities to which they belong. I bring these ideas to life through an …

Artificial Intelligence-Enhanced Predictive Insights For Advancing Financial Inclusion: A Human-Centric Ai-Thinking Approach, Meng Leong How, Sin Mei Cheah, Aik Cheow Khor, Yong Jiet Chan

Research Collection Lee Kong Chian School Of Business

According to the World Bank, a key factor to poverty reduction and improving prosperity is financial inclusion. Financial service providers (FSPs) offering financially-inclusive solutions need to understand how to approach the underserved successfully. The application of artificial intelligence (AI) on legacy data can help FSPs to anticipate how prospective customers may respond when they are approached. However, it remains challenging for FSPs who are not well-versed in computer programming to implement AI projects. This paper proffers a no-coding human-centric AI-based approach to simulate the possible dynamics between the financial profiles of prospective customers collected from 45,211 contact encounters and predict …

A Cue Adaptive Decoder For Controllable Neural Response Generation, Weichao Wang, Shi Feng, Wei Gao, Daling Wang, Yifei Zhang

Research Collection School Of Computing and Information Systems

In open-domain dialogue systems, dialogue cues such as emotion, persona, and emoji can be incorporated into conversation models for strengthening the semantic relevance of generated responses. Existing neural response generation models either incorporate dialogue cue into decoder’s initial state or embed the cue indiscriminately into the state of every generated word, which may cause the gradients of the embedded cue to vanish or disturb the semantic relevance of generated words during back propagation. In this paper, we propose a Cue Adaptive Decoder (CueAD) that aims to dynamically determine the involvement of a cue at each generation step in the decoding. …

Differentially Private Online Task Assignment In Spatial Crowdsourcing: A Tree-Based Approach, Qian Tao, Yongxin Tong, Zimu Zhou, Yexuan Shi, Lei Chen, Ke Xu

Research Collection School Of Computing and Information Systems

With spatial crowdsourcing applications such as Uber and Waze deeply penetrated into everyday life, there is a growing concern to protect user privacy in spatial crowdsourcing. Particularly, locations of workers and tasks should be properly processed via certain privacy mechanism before reporting to the untrusted spatial crowdsourcing server for task assignment. Privacy mechanisms typically permute the location information, which tends to make task assignment ineffective. Prior studies only provide guarantees on privacy protection without assuring the effectiveness of task assignment. In this paper, we investigate privacy protection for online task assignment with the objective of minimizing the total distance, an …

A New Construction For Linkable Secret Handshake, Yangguang Tian, Yingjiu Li, Robert H. Deng, Nan Li, Guomin Yang, Zheng Yang

Research Collection School Of Computing and Information Systems

In this paper, we introduce a new construction for linkable secret handshake that allows authenticated users to perform handshake anonymously within allowable times. We define formal security models for the new construction, and prove that it can achieve session key security, anonymity, untraceability and linkable affiliation-hiding. In particular, the proposed construction ensures that (i) anyone can trace the real identities of dishonest users who perform handshakes for more than k times; and (ii) an optimal communication cost between authorized users is achieved by exploiting the proof of knowledges.

Review-Guided Helpful Answer Identification In E-Commerce, Wenxuan Zhang, Wai Lam, Yang Deng, Jing Ma

Research Collection School Of Computing and Information Systems

Product-specific community question answering platforms can greatly help address the concerns of potential customers. However, the user-provided answers on such platforms often vary a lot in their qualities. Helpfulness votes from the community can indicate the overall quality of the answer, but they are often missing. Accurately predicting the helpfulness of an answer to a given question and thus identifying helpful answers is becoming a demanding need. Since the helpfulness of an answer depends on multiple perspectives instead of only topical relevance investigated in typical QA tasks, common answer selection algorithms are insufficient for tackling this task. In this paper, …

Privacy-Preserving Outsourced Support Vector Machine Design For Secure Drug Discovery, Ximeng Liu, Robert H. Deng, Kim-Kwang Raymond Choo, Yang Yang

Research Collection School Of Computing and Information Systems

In this paper, we propose a framework for privacy-preserving outsourced drug discovery in the cloud, which we refer to as POD. Specifically, POD is designed to allow the cloud to securely use multiple drug formula providers' drug formulas to train Support Vector Machine (SVM) provided by the analytical model provider. In our approach, we design secure computation protocols to allow the cloud server to perform commonly used integer and fraction computations. To securely train the SVM, we design a secure SVM parameter selection protocol to select two SVM parameters and construct a secure sequential minimal optimization protocol to privately refresh …

Voicecoach: Interactive Evidence-Based Training For Voice Modulation Skills In Public Speaking, Xingbo Wang, Haipeng Zeng, Yong Wang, Aoyu Wu, Zhida Sun, Xiaojuan Ma, Qu Huamin

Research Collection School Of Computing and Information Systems

The modulation of voice properties, such as pitch, volume, and speed, is crucial for delivering a successful public speech. However, it is challenging to master different voice modulation skills. Though many guidelines are available, they are often not practical enough to be applied in different public speaking situations, especially for novice speakers. We present VoiceCoach, an interactive evidence-based approach to facilitate the effective training of voice modulation skills. Specifically, we have analyzed the voice modulation skills from 2623 high-quality speeches (i.e., TED Talks) and use them as the benchmark dataset. Given a voice input, VoiceCoach automatically recommends good voice modulation …

Predictive Task Assignment In Spatial Crowdsourcing: A Data-Driven Approach, Yan Zhao, Kai Zheng, Yue Cui, Han Su, Feida Zhu, Xiaofang Zhou

Research Collection School Of Computing and Information Systems

With the rapid development of mobile networks and the widespread usage of mobile devices, spatial crowdsourcing, which refers to assigning location-based tasks to moving workers, has drawn increasing attention. One of the major issues in spatial crowdsourcing is task assignment, which allocates tasks to appropriate workers. However, existing works generally assume the static offline scenarios, where the spatio-temporal information of all the workers and tasks is determined and known a priori. Ignorance of the dynamic spatio-temporal distributions of workers and tasks can often lead to poor assignment results. In this work we study a novel spatial crowdsourcing problem, namely Predictive …

Are These Comments Triggering? Predicting Triggers Of Toxicity In Online Discussions, Hind Almerekhi, Haewoon Kwak, Joni Salminen, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

Understanding the causes or triggers of toxicity adds a new dimension to the prevention of toxic behavior in online discussions. In this research, we define toxicity triggers in online discussions as a non-toxic comment that lead to toxic replies. Then, we build a neural network-based prediction model for toxicity trigger. The prediction model incorporates text-based features and derived features from previous studies that pertain to shifts in sentiment, topic flow, and discussion context. Our findings show that triggers of toxicity contain identifiable features and that incorporating shift features with the discussion context can be detected with a ROC-AUC score of …

Understanding The Relation Between Repeat Developer Interactions And Bug Resolution Times In Large Open Source Ecosystems: A Multisystem Study, Subhajit Datta, Reshma Roychoudhuri, Subhashis Majumder

Research Collection School Of Computing and Information Systems

Large‐scale software systems are being increasingly built by distributed teams of developers who interact across geographies and time zones. Ensuring smooth knowledge transfer and the percolation of skills within and across such teams remain key challenges for organizations. Towards addressing this challenge, organizations often grapple with questions around whether and how repeat collaborations between members of a team relate to outcomes of important activities. In the context of this paper, the word ‘repeat interaction’ does not imply a greater number of interactions; it refers to repeat interaction between a pair of developers who have collaborated before. In this paper, we …

Designing A Smart Internet Of Things Solution For Point Of Use Water Filtration Management System In Residential, Commercial And Public Settings, Tristan Lim, Hwee-Pink Tan, Chin Sin Ong, Rahul Belani, Siddhant S. K. Agrawal

Research Collection School Of Computing and Information Systems

The use of water filtration Point-of-Use (POU) systems are extensive, ranging from water dispensers in public estates, to household POU water systems. Manufacturers typically recommend filtration cartridges to be changed (i) after their useful life, or (ii) when the water flow volume have exceeded certain capacity, whichever is earlier. However, filtration mechanisms are typically not changed with sufficient regularity. Overused filters can result in negative health effects, over and above the deterioration and loss of filtration benefits of the POU water system. Presently most existing water purification systems do not have smart connected Internet of Things (IoT) means of informing …

Attribute-Based Cloud Data Integrity Auditing For Secure Outsourced Storage, Yong Yu, Yannan Li, Bo Yang, Willy Susilo, Guomin Yang, Jian Bai

Research Collection School Of Computing and Information Systems

Outsourced storage such as cloud storage can significantly reduce the burden of data management of data owners. Despite of a long list of merits of cloud storage, it triggers many security risks at the same time. Data integrity, one of the most burning challenges in secure cloud storage, is a fundamental and pivotal element in outsourcing services. Outsourced data auditing protocols enable a verifier to efficiently check the integrity of the outsourced files without downloading the entire file from the cloud, which can dramatically reduce the communication overhead between the cloud server and the verifier. Existing protocols are mostly based …

On The Security Of Lwe Cryptosystem Against Subversion Attacks, Zhichao Yang, Rongmao Chen, Chao Li, Longjiang Qu, Guomin Yang

Research Collection School Of Computing and Information Systems

Subversion of cryptography has received wide attentions especially after the Snowden Revelations in 2013. Most of the currently proposed subversion attacks essentially rely on the freedom of randomness choosing in the cryptographic protocol to hide backdoors embedded in the cryptosystems. Despite the fact that significant progresses in this line of research have been made, most of them mainly considered the classical setting, while the research gap regarding subversion attacks against post-quantum cryptography remains tremendous. Inspired by this observation, we investigate a subversion attack against existing protocol that is proved post-quantum secure. Particularly, we show an efficient way to undetectably subvert …

Improving Neural Relation Extraction With Implicit Mutual Relations, Jun Kuang, Yixin Cao, Jianbing Zheng, Xiangnan He, Ming Gao, Aoying Zhou

Research Collection School Of Computing and Information Systems

Relation extraction (RE) aims at extracting the relation between two entities from the text corpora. It is a crucial task for Knowledge Graph (KG) construction. Most existing methods predict the relation between an entity pair by learning the relation from the training sentences, which contain the targeted entity pair. In contrast to existing distant supervision approaches that suffer from insufficient training corpora to extract relations, our proposal of mining implicit mutual relation from the massive unlabeled corpora transfers the semantic information of entity pairs into the RE model, which is more expressive and semantically plausible. After constructing an entity proximity …

Understanding Cryptocurrencies, Wolfgang Karl Hardle, Campbell R. Harvey, Raphael C. G. Ruele

Sim Kee Boon Institute for Financial Economics

Cryptocurrency refers to a type of digital asset that uses distributed ledger, or blockchain, technology to enable a secure transaction. Although the technology is widely misunderstood, many central banks are considering launching their own national cryptocurrency. In contrast to most data in financial economics, detailed data on the history of every transaction in the cryptocurrency complex are freely available. Furthermore, empirically oriented research is only now beginning, presenting an extraordinary research opportunity for academia. We provide some insights into the mechanics of cryptocurrencies, describing summary statistics and focusing on potential future research avenues in financial economics.

Why Commonality Persists?, Raja Velu, Zhaoque Zhou, Chyng Wen Tee

Research Collection Lee Kong Chian School Of Business

Studies on commonality in returns, order flows and liquidity find that the first principal component is closely aligned with the market factor. With the increasing presence of high-frequency trading, commonality in returns, order flows, and liquidity can potentially arise from the commonality in the interpretation of real-time signals. In this paper, we go beyond the first factor and show that the other dominant principal components consistently reflects investors' herding behavior, demonstrating the multi-dimensional aspect of commonality. Instead of relating the asset returns to order flows, we take both as endogenous, and provide empirical evidence showing that returns commonality is driven …

Dbs Impact Measurement Project: Technical Review, Hao Liang, Phuong Tran Bao Nguyen, David Fernandez, Jun Ho Park

Research Collection Lee Kong Chian School Of Business

The measurement of ESG and its impact is becoming one of the more important and debated issues in sustainable business practice, with the significant challenges being the subjectivity of scope, criteria, as well as lack of consistency across different rating agencies and data providers

Impact measurement goes beyond ESG measurement. Apart from qualitative and input-based approach, it encapsulates a more outcome/impact-based approach, supported with quantitative methods

Impact measurement and valuation are still at the infant stage, with limited research and guidelines, thus [Impact Institute] II’s approach has significant novelty and is among the first to measure and value impact

II …

Time-Series Momentum: Is It There?, Dashan Huang, Jiangyuan Li, Liyao Wang, Guofu Zhou

Research Collection Lee Kong Chian School Of Business

Time-series momentum (TSM) refers to the predictability of the past 12-month return on the next one-month return, and is the focus of several recent influential studies. This paper shows, however, that asset-by-asset time-series regressions reveal little evidence of TSM, both in- and out-of-sample. While the t-statistic in a pooled regression appears large, it is not statistically reliable as it is less than the critical values of parametric and non-parametric bootstraps. From an investment perspective, the TSM strategy is profitable, but its performance is virtually the same as that of a similar strategy that is based on historical sample mean and …

Family Entrenchment And Internal Control: Evidence From S&P 1500 Firms, Xia Chen, Mei Feng, Chan Li

Research Collection School Of Accountancy

We examine whether family owners exploit internal control weaknesses for entrenchment purposes and whether the public disclosure requirement under SOX 404 helps alleviate this entrenchment. We find supportive evidence for both questions. In the initial years of SOX 404 implementation (2004 and 2005), ineffective internal control in family CEO firms is more conducive to entrenchment - measured by the occurrence of misstatements, frauds, and related party transactions - than ineffective internal control in nonfamily firms is. With the public disclosure requirement of SOX 404 in place, family CEO firms are more likely to remediate internal control weaknesses, and the resulting …

What Are You Saying? Using Topic To Detect Financial Misreporting, Nerissa C. Brown, Richard M. Crowley, W. Brooke Elliott

Research Collection School Of Accountancy

We use a machine learning technique to assess whether the thematic content of financial statement disclosures (labeled topic) is incrementally informative in predicting intentional misreporting. Using a Bayesian topic modeling algorithm, we determine and empirically quantify the topic content of a large collection of 10‐K narratives spanning 1994 to 2012. We find that the algorithm produces a valid set of semantically meaningful topics that predict financial misreporting, based on samples of Securities and Exchange Commission (SEC) enforcement actions (Accounting and Auditing Enforcement Releases [AAERs]) and irregularities identified from financial restatements and 10‐K filing amendments. Our out‐of‐sample tests indicate that topic …

Changes In Decision-Making Authority When Chaebol Firms Grow: From The Perspective Of Non-Family Managers, Changhwan Kim

Dissertations and Theses Collection (Open Access)

What changes do non-family managers in large family firms such as chaebols (Korean conglomerates) observe in their decision-making authority when their organizations grow? The intuitive expectation is that non-family managers' decision-making authority will grow in conjunction with the successful expansion of the business and growth of the firm.

Based on 45 in-depth semistructured interviews with non-family managers from a wide range of chaebol firms, this study analyzes how non-family managers perceive the change in their decision-making authority and the cause of this change.

The findings indicate that respondents perceive that their decision-making authority does not increase with the growth of …

The Effect Of Language On Voter Opinion: Results From A Survey Experiment In Thailand, Jacob I. Ricks

Research Collection School of Social Sciences

Politicians have long engaged in marketing themselves by employing distinct speaking styles to signal social standing, competence, or a shared background with their audience. What effect does this use of different language appeals have on voter opinion? Utilizing a survey experiment in Thailand, I test a set of hypotheses about the effect of language on respondent opinions. Relying on three distinct treatments, a formal language register, an informal language register, and an ethnic language, I demonstrate the multiple effects of language on political appeal. The use of a formal register has mixed effects, signaling both high education as well as …

Bayesian Calibration At The Urban Scale: A Case Study On A Large Residential Heating Demand Application In Amsterdam, Cheng-Kai Wang, Simon Tindemans, Clayton Miller, Giorgio Agugiaro, Jantien Stoter

Research Collection College of Integrative Studies

A bottom-up building energy modelling at the urban scale based on Geographic Information System and semantic 3D city models can provide quantitative insights to tackle critical urban energy challenges. Nevertheless, incomplete information is a common obstacle to produce reliable modelling results. The residential building heating demand simulation performance gap caused by input uncertainties is discussed in this study. We present a data-driven urban scale energy modelling framework from open-source data harmonization, sensitivity analysis, heating demand simulation at the postcode level to Bayesian calibration with six years of training data and two years of validation data. Comparing the baseline and the …

Using Knowledge Bases For Question Answering, Yunshi Lan

Dissertations and Theses Collection (Open Access)

A knowledge base (KB) is a well-structured database, which contains many of entities and their relations. With the fast development of large-scale knowledge bases such as Freebase, DBpedia and YAGO, knowledge bases have become an important resource, which can serve many applications, such as dialogue system, textual entailment, question answering and so on. These applications play significant roles in real-world industry.

In this dissertation, we try to explore the entailment information and more general entity-relation information from the KBs. Recognizing textual entailment (RTE) is a task to infer the entailment relations between sentences. We need to decide whether a hypothesis …

How Does Status Affect Performance And Learning From Failure? Evidence From Online Communities, Tengjian Zou

Dissertations and Theses Collection (Open Access)

This dissertation is composed of two essays. In the first essay, I investigate the factors that can alleviate the detrimental effect of hierarchy on team performance. I first show that hierarchy negatively impacts team performance, which is consistent with recent meta-analytic evidence. One mechanism that drives this negative effect is that hierarchy prevents low-ranking members from voicing their potentially valuable insights. Then I propose that team familiarity is one factor that can encourage low-ranking team members to speak up. I contend that team familiarity can be established either by team members’ prior experience in working with one another or can …