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Shortlisting Top-K Assignments, Yimin Lin, Kyriakos Mouratidis
Shortlisting Top-K Assignments, Yimin Lin, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
In this paper we identify a novel query type, the top-K assignment query (αTop-K). Consider a set of objects and a set of suppliers, where each object must be assigned to one supplier. Assume that there is a cost associated with every object-supplier pair. If we allocate each object to the server with the smallest cost (for the specific object), the derived overall assignment will have the minimum total cost. In many scenarios, however, runner-up assignments may be required too, like for example when a decision maker needs to make additional considerations, not captured by individual object-supplier costs. In this …
Popularity, Interoperability, And Impact Of Programming Languages In 100,000 Open Source Projects, Tegawende F. Bissyande, Ferdian Thung, David Lo, Lingxiao Jiang, Laurent Réveillère
Popularity, Interoperability, And Impact Of Programming Languages In 100,000 Open Source Projects, Tegawende F. Bissyande, Ferdian Thung, David Lo, Lingxiao Jiang, Laurent Réveillère
Research Collection School Of Computing and Information Systems
Programming languages have been proposed even before the era of the modern computer. As years have gone, computer resources have increased and application domains have expanded, leading to the proliferation of hundreds of programming languages, each attempting to improve over others or to address new programming paradigms. These languages range from procedural languages like C, object oriented languages like Java, and functional languages such as ML and Haskell. Unfortunately, there is a lack of large scale and comprehensive studies that examine the “popularity”, “interoperability”, and “impact” of various programming languages. To fill this gap, this study investigates a hundred thousands …
Platform Regulation On Seller Heterogeneity, Ruhai Wu, Mei Lin
Platform Regulation On Seller Heterogeneity, Ruhai Wu, Mei Lin
Research Collection School Of Computing and Information Systems
On a "marketplace" platform, where two sides of users trade, the platform owner has an incentive to regulate its marketplace for a higher profit. This study focuses on a monopoly platform's nonpricing, regulatory strategies in governing quality heterogeneity of competing sellers. In contrast to related studies, we endogenize strategic interactions among platform users. Our model extends the circular city model to capture seller heterogeneity in both variety and quality. The closed-form equilibrium solution reveals a ripple effect that exerts competitive pressure from seller to seller at a diminishing magnitude. The equilibrium analysis enables us to connect the economic mechanisms in …
Combining Model Checking And Testing With An Application To Reliability Prediction And Distribution, Lin Gui, Jun Sun, Yang Liu, Yuanjie Si, Jin Song Dong, Xinyu Wang
Combining Model Checking And Testing With An Application To Reliability Prediction And Distribution, Lin Gui, Jun Sun, Yang Liu, Yuanjie Si, Jin Song Dong, Xinyu Wang
Research Collection School Of Computing and Information Systems
Testing provides a probabilistic assurance of system correctness. In general, testing relies on the assumptions that the system under test is deterministic so that test cases can be sampled. However, a challenge arises when a system under test behaves non-deterministiclly in a dynamic operating environment because it will be unknown how to sample test cases.In this work, we propose a method combining hypothesis testing and probabilistic model checking so as to provide the ``assurance" and quantify the error bounds. The idea is to apply hypothesis testing to deterministic system components and use probabilistic model checking techniques to lift the results …
Mkboost: A Framework Of Multiple Kernel Boosting, Hao Xia, Steven C. H. Hoi
Mkboost: A Framework Of Multiple Kernel Boosting, Hao Xia, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Multiple kernel learning (MKL) is a promising family of machine learning algorithms using multiple kernel functions for various challenging data mining tasks. Conventional MKL methods often formulate the problem as an optimization task of learning the optimal combinations of both kernels and classifiers, which usually results in some forms of challenging optimization tasks that are often difficult to be solved. Different from the existing MKL methods, in this paper, we investigate a boosting framework of MKL for classification tasks, i.e., we adopt boosting to solve a variant of MKL problem, which avoids solving the complicated optimization tasks. Specifically, we present …
Real-Life Vehicle Routing With Non-Standard Constraints, Wee Leong Lee
Real-Life Vehicle Routing With Non-Standard Constraints, Wee Leong Lee
Research Collection School Of Computing and Information Systems
Real-life vehicle routing problems comprise of a number of complexities that are not considered by the classical models found in vehicle routing literature. I present, in this paper, a two-stage sweep-based heuristic to find good solutions to a real-life Vehicle Routing Problem (VRP). The problem I shall consider, will deal with some non-standard constraints beyond those normally associated with the classical VRP. Other than considering the capacity constraints for vehicles and the time windows for deliveries, I shall introduce four additional non-standard constraints: merging of customer orders, controlling the maximum number of drop points, matching orders to vehicle types, and …
An Empirical Study Of Adoption Of Software Testing In Open Source Projects, Pavneet Singh Kochhar, Tegawende F. Bissyande, David Lo, Lingxiao Jiang
An Empirical Study Of Adoption Of Software Testing In Open Source Projects, Pavneet Singh Kochhar, Tegawende F. Bissyande, David Lo, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
In software engineering, testing is a crucial activity that is designed to ensure the quality of program code. For this activity, software teams spend substantial resources constructing test cases to thoroughly assess the correctness of software functionality. What is the proportion of open source projects that include test cases? What is the effect of number of developers on the number of test cases? In this study, we explore open source projects and investigate the correlation between the presence of test cases and various project development characteristics, including the number of lines of code, the size of development teams and the …
Gamification Of Education Using Computer Games, Fiona Fui-Hoon Nah, Venkata Telaprolu, Shashank Rallapalli, Pavani R. Venkata
Gamification Of Education Using Computer Games, Fiona Fui-Hoon Nah, Venkata Telaprolu, Shashank Rallapalli, Pavani R. Venkata
Research Collection School Of Computing and Information Systems
We review the literature on gamification and identify principles of gamification and system design elements for gamifying computer educational games. Gamification of education is expected to increase learners’ engagement, which in turn increases learning achievement. We propose a gamification framework that synthesizes findings from the literature. The gamification framework is comprised of principles of gamification, system design elements for gamification, and dimensions of user engagement.
Usability Of Performance Dashboards, Usefulness Of Operational And Tactical Support, And Quality Of Strategic Support: A Research Framework, Bih-Ru Lea, Fiona Fui-Hoon Nah
Usability Of Performance Dashboards, Usefulness Of Operational And Tactical Support, And Quality Of Strategic Support: A Research Framework, Bih-Ru Lea, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Performance dashboards are used as a strategic decision support tool in organizations. In this research, we examine the relationships between the usability of performance dashboards, the usefulness of operational and tactical support, and the quality of strategic support that they provide. We hypothesize that usability of performance dashboards will influence user perceptions of the usefulness of the operational and tactical support provided by the dashboards, which in turn influence the perceived quality of strategic support provided.
Unified Modeling Language: The Teen Years And Growing Pains, J. Erickson, Keng Siau
Unified Modeling Language: The Teen Years And Growing Pains, J. Erickson, Keng Siau
Research Collection School Of Computing and Information Systems
Unified Modeling Language (UML) is adopted by the Object Management Group as a standardized general-purpose modeling language for object-oriented software engineering. Despite its status as a standard, UML is still in a development stage and many studies have highlighted its weaknesses and challenges - including those related to human factor issues. Further, UML has grown considerably more complex since its inception. This paper traces the history of Unified Modeling Language (UML) from its formation to its current state and discusses the current state of the UML language. The paper first introduces UML and its various diagrams, and discusses its characteristics …
Usability Of Performance Dashboards, Usefulness Of Operational And Tactical Support, And Quality Of Strategic Support: A Research Framework, Bih-Ru Lea, Fiona Fui-Hoon Nah
Usability Of Performance Dashboards, Usefulness Of Operational And Tactical Support, And Quality Of Strategic Support: A Research Framework, Bih-Ru Lea, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Performance dashboards are used as a strategic decision support tool in organizations. In this research, we examine the relationships between the usability of performance dashboards, the usefulness of operational and tactical support, and the quality of strategic support that they provide. We hypothesize that usability of performance dashboards will influence user perceptions of the usefulness of the operational and tactical support provided by the dashboards, which in turn influence the perceived quality of strategic support provided.
Using Case Studies To Design And Deliver Technology-Centered Computing Education Courses: An Innovative Approach From An Undergraduate Information Systems Program In Singapore, Ilse Baumgartner
Research Collection School Of Computing and Information Systems
While the advantages of using case studies as an educational vehicle in computing education appear to be more than obvious, there is a very limited amount of research works or practice papers reporting on actual implementations of undergraduate or graduate computing courses which would be largely based on case studies. This conference contribution reports on selected best practices of course design and delivery implemented in one of the core courses of the Bachelor of Science (Information Systems Management) degree program (BSc (ISM)) offered by the School of Information Systems (SIS) at the Singapore Management University (SMU). Nearly all assessments, exercises, …
The Evolution Of Modular Product Architectures And The Emergence Of Platform Ecosystems, C. Jason Woodard, Eric K. Clemons
The Evolution Of Modular Product Architectures And The Emergence Of Platform Ecosystems, C. Jason Woodard, Eric K. Clemons
Research Collection School Of Computing and Information Systems
While a large body of research has examined the advantages and disadvantages of modularity in product design, studies of modularization have tended to focus on settings in which a product’s architecture is determined by a single designer or designers within a single organization. In this paper, we ask whether modularity can arise in a decentralized setting where high-value designs are rewarded but designers’ ability to coordinate with each other and anticipate the consequences of their actions is limited—in short, whether modularity can evolve. To answer this question, we developed an agent-based model in which boundedly rational firms combine components into …
Tesla: An Extended Study Of An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe, Burcin Becerik-Gerber
Tesla: An Extended Study Of An Energy-Saving Agent That Leverages Schedule Flexibility, Jun Young Kwak, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe, Burcin Becerik-Gerber
Research Collection School Of Computing and Information Systems
This paper presents transformative energy-saving schedule-leveraging agent (TESLA), an agent for optimizing energy usage in commercial buildings. TESLA’s key insight is that adding flexibility to event/meeting schedules can lead to significant energy savings. This paper provides four key contributions: (i) online scheduling algorithms, which are at the heart of TESLA, to solve a stochastic mixed integer linear program for energy-efficient scheduling of incrementally/dynamically arriving meetings and events; (ii) an algorithm to effectively identify key meetings that lead to significant energy savings by adjusting their flexibility; (iii) an extensive analysis on energy savings achieved by TESLA; and (iv) surveys of real …
Technique For Authenticating H.264/Svc Streams In Surveillance Applications, Wei Zhuo, Robert H. Deng, Jialie Shen, Yongdong Wu, Xuhua Ding, Swee Won Lo
Technique For Authenticating H.264/Svc Streams In Surveillance Applications, Wei Zhuo, Robert H. Deng, Jialie Shen, Yongdong Wu, Xuhua Ding, Swee Won Lo
Research Collection School Of Computing and Information Systems
Surveillance codestreams coded by H.264/SVC (scalable video coding), which consists of one base layer and one or more enhancement layers, supply flexible and various quality, resolution, and temporal (sub)codestreams such that clients with different network bandwidth and terminal devices can seamlessly access them. In this paper, we present a robust authentication scheme for them in order to insure the integrity of SVC surveillance codestreams, named AUSSC (Authenticating SVC Surveillance Codestreams). AUSSC exploits cryptographic-based authentication for base layer and content-based authentication for enhancement layers. For content-based authentication, AUSSC extracts full features from the first frame of each GOP (group of picture) …
An Empirical Study Of Bugs In Software Build Systems, Xin Xia, Xiaozhen Zhou, David Lo, Xiaoqiong Zhao
An Empirical Study Of Bugs In Software Build Systems, Xin Xia, Xiaozhen Zhou, David Lo, Xiaoqiong Zhao
Research Collection School Of Computing and Information Systems
Build system converts source code, libraries and other data into executable programs by orchestrating the execution of compilers and other tools. The whole building process is managed by a software build system, such as Make, Ant, CMake, Maven, Scons, and QMake. The reliability of software build systems would affect the reliability of the build process. In this paper, we perform an empirical study on bugs in software build systems. We analyze four software build systems, Ant, Maven, CMake and QMake, which are four typical and widely-used software build systems, and can be used to build Java, C, C++ systems. We …
Collective Diffusion Over Networks: Models And Inference, Akshat Kumar, Daniel Sheldon, Biplav Srivastava
Collective Diffusion Over Networks: Models And Inference, Akshat Kumar, Daniel Sheldon, Biplav Srivastava
Research Collection School Of Computing and Information Systems
Diffusion processes in networks are increasingly used to model the spread of information and social influence. In several applications in computational sustainability such as the spread of wildlife, infectious diseases and traffic mobility pattern, the observed data often consists of only aggregate information. In this work, we present new models that generalize standard diffusion processes to such collective settings. We also present optimization based techniques that can accurately learn the underlying dynamics of the given contagion process, including the hidden network structure, by only observing the time a node becomes active and the associated aggregate information. Empirically, our technique is …
Active Learning With Expert Advice, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang
Active Learning With Expert Advice, Peilin Zhao, Steven C. H. Hoi, Jinfeng Zhuang
Research Collection School Of Computing and Information Systems
Conventional learning with expert advice methods assumes a learner is always receiving the outcome (e.g., class labels) of every incoming training instance at the end of each trial. In real applications, acquiring the outcome from oracle can be costly or time consuming. In this paper, we address a new problem of active learning with expert advice, where the outcome of an instance is disclosed only when it is requested by the online learner. Our goal is to learn an accurate prediction model by asking the oracle the number of questions as small as possible. To address this challenge, we propose …
Keystroke Timing Analysis Of On-The-Fly Web Apps, Chee Meng Tey, Payas Gupta, Debin Gao, Yan Zhang
Keystroke Timing Analysis Of On-The-Fly Web Apps, Chee Meng Tey, Payas Gupta, Debin Gao, Yan Zhang
Research Collection School Of Computing and Information Systems
The Google Suggestions service used in Google Search is one example of an interactivity rich Javascript application. In this paper, we analyse the timing side channel of Google Suggestions by reverse engineering the communication model from obfuscated Javascript code. We consider an attacker who attempts to infer the typing pattern of a victim. From our experiments involving 11 participants, we found that for each keypair with at least 20 samples, the mean of the inter-keystroke timing can be determined with an error of less than 20%.
Demo: Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song
Demo: Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song
Research Collection School Of Computing and Information Systems
In this demo, we introduce SocioPhone, a novel initiative toward everyday face-to-face interaction monitoring platform. Among diverse verbal, aural, visual cues expressed during face-to-face interaction, SocioPhone captures diverse meta-linguistic information from conversations and provides interaction-aware applications on-the-fly. Undoubtedly, conversations are a key channel for face-to-face interaction. Specifically, monitoring conversational turns, i.e., alternation of different speakers (including none speaking), is the first crucial step to derive diverse interesting aspects of conversations, e.g., who is talking right now, how long and often one talks, how quickly one responds to another, and so on. In this demo, we will show the core technique …
Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni
Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni
Research Collection School Of Computing and Information Systems
The Last Mile Problem (LMP) refers to the provision of travel service from thenearest public transportation node to a home or office. We study the supply side of thisproblem in a stochastic setting, with batch demands resulting from the arrival of groupsof passengers at rail stations or bus stops who request last-mile service. Closed-formbounds and approximations are derived for the performance of Last Mile TransportationsSystems as a function of the fundamental design parameters of such systems. An initialset of results is obtained for the case in which a fleet of vehicles of unit capacity providesthe Last Mile service and each …
Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song
Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song
Research Collection School Of Computing and Information Systems
In this paper, we propose SocioPhone, a novel initiative to build a mobile platform for face-to-face interaction monitoring. Face-to-face interaction, especially conversation, is a fundamental part of everyday life. Interaction-aware applications aimed at facilitating group conversations have been proposed, but have not proliferated yet. Useful contexts to capture and support face-to-face interactions need to be explored more deeply. More important, recognizing delicate conversational contexts with commodity mobile devices requires solving a number of technical challenges. As a first step to address such challenges, we identify useful meta-linguistic contexts of conversation, such as turn-takings, prosodic features, a dominant participant, and pace. …
Visual Tracking Via Locality Sensitive Histograms, Shengfeng He, Qingxiong Yang, Rynson W.H. Lau, Jian Wang, Ming-Hsuan Yang
Visual Tracking Via Locality Sensitive Histograms, Shengfeng He, Qingxiong Yang, Rynson W.H. Lau, Jian Wang, Ming-Hsuan Yang
Research Collection School Of Computing and Information Systems
This paper presents a novel locality sensitive histogram algorithm for visual tracking. Unlike the conventional image histogram that counts the frequency of occurrences of each intensity value by adding ones to the corresponding bin, a locality sensitive histogram is computed at each pixel location and a floating-point value is added to the corresponding bin for each occurrence of an intensity value. The floating-point value declines exponentially with respect to the distance to the pixel location where the histogram is computed, thus every pixel is considered but those that are far away can be neglected due to the very small weights …
A Direct Mining Approach To Efficient Constrained Graph Pattern Discovery, Feida Zhu, Zequn Zhang, Qiang Qu
A Direct Mining Approach To Efficient Constrained Graph Pattern Discovery, Feida Zhu, Zequn Zhang, Qiang Qu
Research Collection School Of Computing and Information Systems
Despite the wealth of research on frequent graph pattern mining, how to efficiently mine the complete set of those with constraints still poses a huge challenge to the existing algorithms mainly due to the inherent bottleneck in the mining paradigm. In essence, mining requests with explicitly-specified constraints cannot be handled in a way that is direct and precise. In this paper, we propose a direct mining framework to solve the problem and illustrate our ideas in the context of a particular type of constrained frequent patterns — the “skinny” patterns, which are graph patterns with a long backbone from which …
Experiences With Performance Tradeoffs In Practical, Continuous Indoor Localization, Azeem J. Khan, Vikash Ranjan, Trung-Tuan Luong, Rajesh Krishna Balan, Archan Misra
Experiences With Performance Tradeoffs In Practical, Continuous Indoor Localization, Azeem J. Khan, Vikash Ranjan, Trung-Tuan Luong, Rajesh Krishna Balan, Archan Misra
Research Collection School Of Computing and Information Systems
This paper describes our experiences and observations with the first version of a localization system that continuous tracks the indoor location of a large number of consumer mobile devices. Unlike past work that focuses principally on the accuracy of the location tracking algorithm, we study the performance of the localization system in terms of key additional metrics: scalability and energy-efficiency, which can sometimes conflict with the desire for high accuracy. To ensure that our solution can handle both Android and iOS-based mobile devices (& other closed mobile platforms), we adapt the conventional client-side fingerprinting-based localization approaches to develop a novel …
A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang
A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang
Research Collection School Of Computing and Information Systems
Threaded discussion forums provide an important social media platform. Its rich user generated content has served as an important source of public feedback. To automatically discover the viewpoints or stances on hot issues from forum threads is an important and useful task. In this paper, we propose a novel latent variable model for viewpoint discovery from threaded forum posts. Our model is a principled generative latent variable model which captures three important factors: viewpoint specific topic preference, user identity and user interactions. Evaluation results show that our model clearly outperforms a number of baseline models in terms of both clustering …
Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang
Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang
Research Collection School Of Computing and Information Systems
Advances in sentiment analysis have enabled extraction of user relations implied in online textual exchanges such as forum posts. However, recent studies in this direction only consider direct relation extraction from text. As user interactions can be sparse in online discussions, we propose to apply collaborative filtering through probabilistic matrix factorization to generalize and improve the opinion matrices extracted from forum posts. Experiments with two tasks show that the learned latent factor representation can give good performance on a relation polarity prediction task and improve the performance of a subgroup detection task.
Energy-Efficient Collaborative Query Processing Framework For Mobile Sensing Services, Jin Yang, Tianli Mo, Lipyeow Lim, Kai Uwe Sattler, Archan Misra
Energy-Efficient Collaborative Query Processing Framework For Mobile Sensing Services, Jin Yang, Tianli Mo, Lipyeow Lim, Kai Uwe Sattler, Archan Misra
Research Collection School Of Computing and Information Systems
Many emerging context-aware mobile applications involve the execution of continuous queries over sensor data streams generated by a variety of on-board sensors on multiple personal mobile devices (aka smartphones). To reduce the energyoverheads of such large-scale, continuous mobile sensing and query processing, this paper introduces CQP, a collaborative query processing framework that exploits the overlap (in both the sensor sources and the query predicates) across multiple smartphones. The framework automatically identifies the shareable parts of multiple executing queries, and then reduces the overheads of repetitive execution and data transmissions, by having a set of 'leader' mobile nodes execute and disseminate …
Think Twice Before You Share: Analyzing Privacy Leakage Under Privacy Control In Online Social Networks, Yan Li, Yingjiu Li, Qiang Yan, Robert H. Deng
Think Twice Before You Share: Analyzing Privacy Leakage Under Privacy Control In Online Social Networks, Yan Li, Yingjiu Li, Qiang Yan, Robert H. Deng
Research Collection School Of Computing and Information Systems
Online Social Networks (OSNs) have become one of the major platforms for social interactions. Privacy control is deployed in popular OSNs to protect user’s data. However, user’s sensitive information could still be leaked even when privacy rules are properly configured. We investigate the effectiveness of privacy control against privacy leakage from the perspective of information flow. Our analysis reveals that the existing privacy control mechanisms do not protect the flow of personal information effectively. By examining typical OSNs including Facebook, Google+, and Twitter, we discover a series of privacy exploits which are caused by the conflicts between privacy control and …
Launching Generic Attacks On Ios With Approved Third-Party Applications, Jin Han, Mon Kywe Su, Qiang Yan, Feng Bao, Robert H. Deng, Debin Gao, Yingjiu Li, Jianying Zhou
Launching Generic Attacks On Ios With Approved Third-Party Applications, Jin Han, Mon Kywe Su, Qiang Yan, Feng Bao, Robert H. Deng, Debin Gao, Yingjiu Li, Jianying Zhou
Research Collection School Of Computing and Information Systems
iOS is Apple’s mobile operating system, which is used on iPhone, iPad and iPod touch. Any third-party applications developed for iOS devices are required to go through Apple’s application vetting process and appear on the official iTunes App Store upon approval.When an application is downloaded from the store and installed on an iOS device, it is given a limited set of privileges, which are enforced by iOS application sandbox. Although details of the vetting process and the sandbox are kept as black box by Apple, it was generally believed that these iOS security mechanisms are effective in defending against malwares. …