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Articles 5401 - 5430 of 9025
Full-Text Articles in Computer Sciences
An Intelligent System For Personalized Conference Event Recommendation And Scheduling, Aldy Gunawan, Hoong Chuin Lau, Pradeep Varakantham, Wenjie Wang
An Intelligent System For Personalized Conference Event Recommendation And Scheduling, Aldy Gunawan, Hoong Chuin Lau, Pradeep Varakantham, Wenjie Wang
Research Collection School Of Computing and Information Systems
Many conference mobile apps today lack the intelligent feature to automatically generates optimal schedules based on delegates' preferences. This entails two major challenges: (a) identifying preferences of users; and (b) given the preferences, generating a schedule that optimizes his preferences. In this paper, we specifically focus on academic conferences, where users are prompted to input their preferred keywords. Our key contribution is an integrated conference scheduling agent that automatically recognizes user preferences based on keywords, provides a list of recommended talks and optimizes user schedule based on these preferences. To demonstrate the utility of our integrated conference scheduling agent, we …
A Reinforcement Learning Framework For Trajectory Prediction Under Uncertainty And Budget Constraint, Truc Viet Le, Siyuan Liu, Hoong Chuin Lau
A Reinforcement Learning Framework For Trajectory Prediction Under Uncertainty And Budget Constraint, Truc Viet Le, Siyuan Liu, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We consider the problem of trajectory prediction, where a trajectory is an ordered sequence of location visits and corresponding timestamps. The problem arises when an agent makes sequential decisions to visit a set of spatial locations of interest. Each location bears a stochastic utility and the agent has a limited budget to spend. Given the agent's observed partial trajectory, our goal is to predict the agent's remaining trajectory. We propose a solution framework to the problem that incorporates both the stochastic utility of each location and the budget constraint. We first cluster the agents into groups of homogeneous behaviors called …
When A Friend Online Is More Than A Friend In Life: Intimate Relationship Prediction In Microblogs, Yunshi Lan, Mengqi Zhang, Feida Zhu, Jing Jiang, Ee-Peng Lim
When A Friend Online Is More Than A Friend In Life: Intimate Relationship Prediction In Microblogs, Yunshi Lan, Mengqi Zhang, Feida Zhu, Jing Jiang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Microblogging services such as Twitter and Sina Weibo have been an important, if not indespensible, platform for people around the world to connect to one another. The rich content and user interactions on these platforms reveal insightful information about each user that are valuable for various real-life applications. In particular, user offline relationships, especially those intimate ones such as family members and couples, offer distinctive value for many business and social settings. In this study, we focus on using Sina Weibo to discover intimate offline relationships among users. The problem is uniquely interesting and challenging due to the difficulty in …
Dynamic-Music: Accurate Device-Free Indoor Localization, Xiang Li, Shengjie Li, Daqing Zhang, Jie Xiong, Yasha Wang, Hong Mei
Dynamic-Music: Accurate Device-Free Indoor Localization, Xiang Li, Shengjie Li, Daqing Zhang, Jie Xiong, Yasha Wang, Hong Mei
Research Collection School Of Computing and Information Systems
Device-free passive indoor localization is playing a critical role in many applications such as elderly care, intrusion detection, smart home, etc. However, existing device-free localization systems either suffer from labor-intensive offline training or require dedicated special-purpose devices. To address the challenges, we present our system named MaTrack, which is implemented on commodity off-the-shelf Intel 5300 Wi-Fi cards. MaTrack proposes a novel Dynamic-MUSIC method to detect the subtle reflection signals from human body and further differentiate them from those reflected signals from static objects (furniture, walls, etc.) to identify the human target's angle for localization. MaTrack does not require any offline …
Control Flow Integrity Enforcement With Dynamic Code Optimization, Yan Lin, Xiaoxiao Tang, Debin Gao, Jianming Fu
Control Flow Integrity Enforcement With Dynamic Code Optimization, Yan Lin, Xiaoxiao Tang, Debin Gao, Jianming Fu
Research Collection School Of Computing and Information Systems
Control Flow Integrity (CFI) is an attractive security property with which most injected and code reuse attacks can be defeated, including advanced attacking techniques like Return-Oriented Programming (ROP). However, comprehensive enforcement of CFI is expensive due to additional supports needed (e.g., compiler support and presence of relocation or debug information) and performance overhead. Recent research has been trying to strike the balance among reasonable approximation of the CFI properties, minimal additional supports needed, and acceptable performance. We investigate existing dynamic code optimization techniques and find that they provide an architecture on which CFI can be enforced effectively and efficiently. In …
Soft Confidence-Weighted Learning, Jialei Wang, Peilin Zhao, Hoi, Steven C. H.
Soft Confidence-Weighted Learning, Jialei Wang, Peilin Zhao, Hoi, Steven C. H.
Research Collection School Of Computing and Information Systems
Online learning plays an important role in many big datamining problems because of its high efficiency and scalability. In theliterature, many online learning algorithms using gradient information havebeen applied to solve online classification problems. Recently, more effectivesecond-order algorithms have been proposed, where the correlation between thefeatures is utilized to improve the learning efficiency. Among them,Confidence-Weighted (CW) learning algorithms are very effective, which assumethat the classification model is drawn from a Gaussian distribution, whichenables the model to be effectively updated with the second-order informationof the data stream. Despite being studied actively, these CW algorithms cannothandle nonseparable datasets and noisy datasets very …
Mining Revision Histories To Detect Cross-Language Clones Without Intermediates, Lingxiao Jiang, Zhiming Peng, Lingxiao Jiang, Hao Zhong, Haibo Yu, Jianjun Zhao
Mining Revision Histories To Detect Cross-Language Clones Without Intermediates, Lingxiao Jiang, Zhiming Peng, Lingxiao Jiang, Hao Zhong, Haibo Yu, Jianjun Zhao
Research Collection School Of Computing and Information Systems
To attract more users on different platforms, many projects release their versions in multiple programming languages (e.g., Java and C#). They typically have many code snippets that implement similar functionalities, i.e., cross-language clones. Programmers often need to track and modify cross-language clones consistently to maintain similar functionalities across different language implementations. In literature, researchers have proposed approaches to detect cross-language clones, mostly for languages that share a common intermediate language (such as the .NET language family) so that techniques for detecting single-language clones can be applied. As a result, those approaches cannot detect cross-language clones for many projects that are …
On The Feasibility Of Detecting Cross-Platform Code Clones Via Identifier Similarity, Xiao Cheng, Lingxiao Jiang, Hao Zhong, Haibo Yu, Jianjun Zhao
On The Feasibility Of Detecting Cross-Platform Code Clones Via Identifier Similarity, Xiao Cheng, Lingxiao Jiang, Hao Zhong, Haibo Yu, Jianjun Zhao
Research Collection School Of Computing and Information Systems
More and more mobile applications run on multiple mobile operating systems to attract more users of different platforms. Although versions on different platforms are implemented in different programming languages (e.g., Java and Objective-C), there must be many code snippets that implement the similar business logic on different platforms. Such code snippets are called cross-platform clones. It is challenging but essential to detect such clones for software maintenance. Due to the practice that developers usually use some common identifiers when implementing the same business logic on different platforms, in this paper, we investigate the identifier similarity of the same mobile application …
Detecting Community Pacemakers Of Burst Topic In Twitter, Guozhong Dong, Wu Yang, Feida Zhu, Wei Wang
Detecting Community Pacemakers Of Burst Topic In Twitter, Guozhong Dong, Wu Yang, Feida Zhu, Wei Wang
Research Collection School Of Computing and Information Systems
Twitter has become one of largest social networks for users to broad-cast burst topics. Influential users usually have a large number of followers and play an important role in the diffusion of burst topic. There have been many studies on how to detect influential users. However, traditional influential users detection approaches have largely ignored influential users in user community. In this paper, we investigate the problem of detecting community pacemakers. Community pacemakers are defined as the influential users that promote early diffusion in the user community of burst topic. To solve this problem, we present DCPBT, a framework that can …
Efficient Community Maintenance For Dynamic Social Networks, Hongchao Qin, Ye Yuan, Feida Zhu, Guoren Wang
Efficient Community Maintenance For Dynamic Social Networks, Hongchao Qin, Ye Yuan, Feida Zhu, Guoren Wang
Research Collection School Of Computing and Information Systems
Community detection plays an important role in a wide range of research topics for social networks including personalized recommendation services and information dissemination. The highly dynamic nature of social platforms, and accordingly the constant updates to the underlying network, all present a serious challenge for efficient maintenance of the identified communities. How to avoid computing from scratch the whole community detection result in face of every update, which constitutes small changes more often than not. To solve this problem, we propose a novel and efficient algorithm to maintain the communities in dynamic social networks by identifying and updating only those …
Extracting Food Substitutes From Food Diary Via Distributional Similarity, Palakorn Achananuparp, Ingmar Weber
Extracting Food Substitutes From Food Diary Via Distributional Similarity, Palakorn Achananuparp, Ingmar Weber
Research Collection School Of Computing and Information Systems
In this paper, we explore the problem of identifying substitute relationship between food pairs from real-world food consumption data as the first step towards the healthier food recommendation. Our method is inspired by the distributional hypothesis in linguistics. Specifically, we assume that foods that are consumed in similar contexts are more likely to be similar dietarily. For example, a turkey sandwich can be considered a suitable substitute for a chicken sandwich if both tend to be consumed with french fries and salad. To evaluate our method, we constructed a real-world food consumption dataset from MyFitnessPal's public food diary entries and …
Cross-Cultural User Perceptions Of Website Design And Security: Introduction To A Commentary And Response On Cyr (2013), Robert John Kauffman
Cross-Cultural User Perceptions Of Website Design And Security: Introduction To A Commentary And Response On Cyr (2013), Robert John Kauffman
Research Collection School Of Computing and Information Systems
Just as the well-known statistician, George Box, commented in a 1978 paper, “All models are wrong, but some are useful,” so are there many ways to design research inquiry approaches to explore issues in various e-commerce contexts – all useful too. In the two brief essays that follow, the reader will see a written commentary and a response that illustrates this idea. It occurred between a technology researcher who published an article on cross-cultural issues in website design in Cyr (2013), and an economist who is able to offer useful insights on the statistical work and data analytics with methods …
Trustworthy Authentication On Scalable Surveillance Video With Background Model Support, Zhuo Wei, Zheng Yan, Yongdong Wu, Robert H. Deng
Trustworthy Authentication On Scalable Surveillance Video With Background Model Support, Zhuo Wei, Zheng Yan, Yongdong Wu, Robert H. Deng
Research Collection School Of Computing and Information Systems
H.264/SVC (Scalable Video Coding) codestreams, which consist of a single base layer and multiple enhancement layers, are designed for quality, spatial, and temporal scalabilities. They can be transmitted over networks of different bandwidths and seamlessly accessed by various terminal devices. With a huge amount of video surveillance and various devices becoming an integral part of the security infrastructure, the industry is currently starting to use the SVC standard to process digital video for surveillance applications such that clients with different network bandwidth connections and display capabilities can seamlessly access various SVC surveillance (sub)codestreams. In order to guarantee the trustworthiness and …
A Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Archan Misra, Randy Tandriansyah Daratan, Thivya Kandappu
A Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Archan Misra, Randy Tandriansyah Daratan, Thivya Kandappu
Research Collection School Of Computing and Information Systems
By effectively utilizing smartphones to reach out and engage a large population of mobile users, mobile crowdsourcing can become a game-changer for many urban operations, such as last mile logistics and municipal monitoring. To overcome the uncertainties and risks associated with a purely best-effort, opportunistic model of such crowdsourcing, we advocate a more centrally-coordinated approach, that (a) takes into account the predicted movement paths of workers and (b) factors in typical human behavioral responses to various incentives and deadlines. To experimentally tackle these challenges, we design, develop and experiment with a real-world mobile crowd-Tasking platform on an urban campus in …
Microblogging Content Propagation Modeling Using Topic-Specific Behavioral Factors, Tuan Anh Hoang, Ee-Peng Lim
Microblogging Content Propagation Modeling Using Topic-Specific Behavioral Factors, Tuan Anh Hoang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
When a microblogging user adopts some content propagated to her, we can attribute that to three behavioral factors, namely, topic virality, user virality, and user susceptibility. Topic virality measures the degree to which a topic attracts propagations by users. User virality and susceptibility refer to the ability of a user to propagate content to other users, and the propensity of a user adopting content propagated to her, respectively. In this paper, we study the problem of mining these behavioral factors specific to topics from microblogging content propagation data. We first construct a three dimensional tensor for representing the propagation instances. …
What Security Questions Do Developers Ask? A Large-Scale Study Of Stack Overflow Posts, Xinli Yang, David Lo, Xin Xia, Zhi-Yuan Wan, Jian-Ling Sun
What Security Questions Do Developers Ask? A Large-Scale Study Of Stack Overflow Posts, Xinli Yang, David Lo, Xin Xia, Zhi-Yuan Wan, Jian-Ling Sun
Research Collection School Of Computing and Information Systems
Security has always been a popular and critical topic. With the rapid development of information technology, it is always attracting people’s attention. However, since security has a long history, it covers a wide range of topics which change a lot, from classic cryptography to recently popular mobile security. There is a need to investigate security-related topics and trends, which can be a guide for security researchers, security educators and security practitioners. To address the above-mentioned need, in this paper, we conduct a large-scale study on security-related questions on Stack Overflow. Stack Overflow is a popular on-line question and answer site …
Predicting Crashing Releases Of Mobile Applications, Xin Xia, Emad Shihab, Yasutaka Kamei, David Lo, Xinyu Wang
Predicting Crashing Releases Of Mobile Applications, Xin Xia, Emad Shihab, Yasutaka Kamei, David Lo, Xinyu Wang
Research Collection School Of Computing and Information Systems
Context: The quality of mobile applications has a vital impact on their user's experience, ratings and ultimately overall success. Given the high competition in the mobile application market, i.e., many mobile applications perform the same or similar functionality, users of mobile apps tend to be less tolerant to quality issues. Goal: Therefore, identifying these crashing releases early on so that they can be avoided will help mobile app developers keep their user base and ensure the overall success of their apps. Method: To help mobile developers, we use machine learning techniques to effectively predict mobile app releases that are more …
How Practitioners Perceive The Relevance Of Esem Research, Jeffrey C. Carver, Oscar Dieste, Nicholas A. Kraft, David Lo, Thomas Zimmermann
How Practitioners Perceive The Relevance Of Esem Research, Jeffrey C. Carver, Oscar Dieste, Nicholas A. Kraft, David Lo, Thomas Zimmermann
Research Collection School Of Computing and Information Systems
Background: The relevance of ESEM research to industry practitioners is key to the long-term health of the conference. Aims: The goal of this work is to understand how ESEM research is perceived within the practitioner community and provide feedback to the ESEM community ensure our research remains relevant. Method: To understand how practitioners perceive ESEM research, we replicated previous work by sending a survey to several hundred industry practitioners at a number of companies around the world. We asked the survey participants to rate the relevance of the research described in 156 ESEM papers published between 2011 and 2015. Results: …
Is Only One Gps Position Sufficient To Locate You To The Road Network Accurately?, Hao Wu, Weiwei Sun, Baihua Zheng
Is Only One Gps Position Sufficient To Locate You To The Road Network Accurately?, Hao Wu, Weiwei Sun, Baihua Zheng
Research Collection School Of Computing and Information Systems
Locating only one GPS position to a road segment accurately is crucial to many location-based services such as mobile taxihailing service, geo-tagging, POI check-in, etc. This problem is challenging because of errors including the GPS errors and the digital map errors (misalignment and the same representation of bidirectional roads) and a lack of context information. To the best of our knowledge, no existing work studies this problem directly and the work to reduce GPS signal errors by considering hardware aspect is the most relevant. Consequently, this work is the first attempt to solve the problem of locating one GPS position …
Automated Bug Report Field Reassignment And Refinement Prediction, Xin Xia, David Lo, Emad Shihab, Xinyu Wang
Automated Bug Report Field Reassignment And Refinement Prediction, Xin Xia, David Lo, Emad Shihab, Xinyu Wang
Research Collection School Of Computing and Information Systems
Bug fixing is one of the most important activities in software development and maintenance. Bugs are reported, recorded, and managed in bug tracking systems such as Bugzilla. In general, a bug report contains many fields, such as product, component, severity, priority, fixer, operating system (OS), and platform, which provide important information for the bug triaging and fixing process. Our previous study finds that approximately 80% of bug reports have their fields reassigned and refined at least once, and bugs with reassigned and refined fields take more time to fix than bugs with no reassigned and refined fields. Thus, automatically predicting …
Towards Autonomous Behavior Learning Of Non-Player Characters In Games, Shu Feng, Ah-Hwee Tan
Towards Autonomous Behavior Learning Of Non-Player Characters In Games, Shu Feng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Non-Player-Characters (NPCs), as found in computer games, can be modelled as intelligent systems, which serve to improve the interactivity and playability of the games. Although reinforcement learning (RL) has been a promising approach to creating the behavior models of non-player characters (NPC), an initial stage of exploration and low performance is typically required. On the other hand, imitative learning (IL) is an effective approach to pre-building a NPC’s behavior model by observing the opponent’s actions, but learning by imitation limits the agent’s performance to that of its opponents. In view of their complementary strengths, this paper proposes a computational model …
High Correlation Of Middle East Respiratory Syndrome Spread With Google Search And Twitter Trends In Korea, Soo-Yong Shin, Dong-Woo Seo, Jisun An, Haewoon Kwak, Sung-Han Kim, Jin Gwack, Min-Woo Jo
High Correlation Of Middle East Respiratory Syndrome Spread With Google Search And Twitter Trends In Korea, Soo-Yong Shin, Dong-Woo Seo, Jisun An, Haewoon Kwak, Sung-Han Kim, Jin Gwack, Min-Woo Jo
Research Collection School Of Computing and Information Systems
The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015, resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance system based on web searches and social media data to monitor this MERS outbreak. We collected the number of daily laboratory-confirmed MERS cases and quarantined cases from May 11, 2015 to June 26, 2015 using the Korean government MERS portal. The daily trends observed via Google search and Twitter during the same time period were also ascertained using Google Trends and Topsy. Correlations among the data were then examined using Spearman …
Fast Covariant Vlad For Image Search, Wan-Lei Zhao, Chong-Wah Ngo, Hanzi Wang
Fast Covariant Vlad For Image Search, Wan-Lei Zhao, Chong-Wah Ngo, Hanzi Wang
Research Collection School Of Computing and Information Systems
Vector of locally aggregated descriptor (VLAD) is a popular image encoding approach for its simplicity and better scalability over conventional bag-of-visual-word approach. In order to enhance its distinctiveness and geometric invariance, covariant VLAD (CVLAD) is proposed to pool local features based on their dominant orientations/characteristic scales, which leads to a geometric-aware representation. This representation achieves rotation/scale invariance when being associated with circular matching. However, the circular matching induces several times of computation overhead, which makes CVLAD hardly suitable for large-scale retrieval tasks. In this paper, the issue of computation overhead is alleviated by performing the circular matching in CVLAD's frequency …
Leveraging Competency Framework To Improve Teaching And Learning: A Methodological Approach, Venky Shankararaman, Joelle Elmaleh
Leveraging Competency Framework To Improve Teaching And Learning: A Methodological Approach, Venky Shankararaman, Joelle Elmaleh
Research Collection School Of Computing and Information Systems
A number of engineering education programs have defined learning outcomes and course-level competencies, and conducted assessments at the program level to determine areas for continuous improvement. However, many of these programs have not implemented a comprehensive competency framework to support the actual delivery and assessment of an individual course. This paper highlights how a competency framework can be used across the life cycle of a course to effectively deliver and assess course content, and give valuable, timely feedback to students thus, improving teaching, student motivation and learning. A framework for leveraging course competencies during course design and delivery is presented, …
Topic Extraction From Microblog Posts Using Conversation Structures, Jing Li, Ming Liao, Wei Gao, Yulan He, Kam-Fai Wong
Topic Extraction From Microblog Posts Using Conversation Structures, Jing Li, Ming Liao, Wei Gao, Yulan He, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Conventional topic models are ineffective for topic extraction from microblog messages since the lack of structure and context among the posts renders poor message-level word co-occurrence patterns. In this work, we organize microblog posts as conversation trees based on reposting and replying relations, which enrich context information to alleviate data sparseness. Our model generates words according to topic dependencies derived from the conversation structures. In specific, we differentiate messages as leader messages, which initiate key aspects of previously focused topics or shift the focus to different topics, and follower messages that do not introduce any new information but simply echo …
A Novel Digital Image Classification Algorithm Via Low-Rank Sparse Bag-Of-Features Model, Xiu-Ming Zou, Huai-Jiang Sun, Sai Yang, Yan Zhu
A Novel Digital Image Classification Algorithm Via Low-Rank Sparse Bag-Of-Features Model, Xiu-Ming Zou, Huai-Jiang Sun, Sai Yang, Yan Zhu
Research Collection School of Computing and Information Systems
Bag-of-features (BoF) is one of the most well-known methods used to represent digital image features because of its simplicity and efficiency. A variety of improved algorithms have been employed to enhance the performance of BoF in characterization. However, challenges in the application of BoF in the field still exist. This study focused on BoF by decomposing local features and presented a novel framework for BoF on the basis of low-rank and sparse matrix decomposition to obtain a more robust and discriminative digital image classification. First, the local feature matrix of a digital image is decomposed into a low-rank matrix and …
Profiling Social Media Users With Selective Self-Disclosure Behavior, Wei Gong
Profiling Social Media Users With Selective Self-Disclosure Behavior, Wei Gong
Dissertations and Theses Collection
Social media has become a popular platform for millions of users to share activities and thoughts. Many applications are now tapping on social media to disseminate information (e.g., news), to promote products (e.g., advertisements), to manage customer relationship (e.g., customer feedback), and to source for investment (e.g., crowdfunding). Many of these applications require user profile knowledge to select the target social media users or to personalize messages to users. Social media user profiling is a task of constructing user profiles such as demographical labels, interests, and opinions, etc., using social media data. Among the social media user profiling research works, …
Decision Modeling And Empirical Analysis Of Mobile Financial Services, Jun Liu
Decision Modeling And Empirical Analysis Of Mobile Financial Services, Jun Liu
Dissertations and Theses Collection
The past twenty years have been a time of many new technological developments, changing business practices, and interesting innovations in the financial information system (IS) and technology landscape. As the financial services industry has been undergoing the digital transformation, the emergence of mobile financial services has been changing the way that customers pay for goods and services purchases and interact with financial institutions. This dissertation seeks to understand the evolution of the mobile payments technology ecosystem and how firms make mobile payments investment decisions under uncertainty, as well as examines the influence of mobile banking on customer behavior and financial …
Unsupervised Multi-Graph Cross-Modal Hashing For Large-Scale Multimedia Retrieval, Liang Xie, Lei Zhu, Guoqi Chen
Unsupervised Multi-Graph Cross-Modal Hashing For Large-Scale Multimedia Retrieval, Liang Xie, Lei Zhu, Guoqi Chen
Research Collection School Of Computing and Information Systems
With the advance of internet and multimedia technologies, large-scale multi-modal representation techniques such as cross-modal hashing, are increasingly demanded for multimedia retrieval. In cross-modal hashing, three essential problems should be seriously considered. The first is that effective cross-modal relationship should be learned from training data with scarce label information. The second is that appropriate weights should be assigned for different modalities to reflect their importance. The last is the scalability of training process which is usually ignored by previous methods. In this paper, we propose Multi-graph Cross-modal Hashing (MGCMH) by comprehensively considering these three points. MGCMH is unsupervised method which …
Design And Evaluation Of Advanced Collusion Attacks On Collaborative Intrusion Detection Networks In Practice, Weizhi Meng, Xiapu Luo, Wenjuan Li, Yan Li
Design And Evaluation Of Advanced Collusion Attacks On Collaborative Intrusion Detection Networks In Practice, Weizhi Meng, Xiapu Luo, Wenjuan Li, Yan Li
Research Collection School Of Computing and Information Systems
To encourage collaboration among single intrusion detection systems (IDSs), collaborative intrusion detection networks (CIDNs) have been developed that enable different IDS nodes to communicate information with each other. This distributed network infrastructure aims to improve the detection performance of a single IDS, but may suffer from various insider attacks like collusion attacks, where several malicious nodes can collaborate to perform adversary actions. To defend against insider threats, challenge-based trust mechanisms have been proposed in the literature and proven to be robust against collusion attacks. However, we identify that such mechanisms depend heavily on an assumption of malicious nodes, which is …