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Full-Text Articles in Entire DC Network
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. …
T-Watcher: A New Visual Analytic System For Effective Traffic Surveillance, Jiansu Pu, Siyuan Liu, Ye Ding, Huamin Qu, Lionel Ni
T-Watcher: A New Visual Analytic System For Effective Traffic Surveillance, Jiansu Pu, Siyuan Liu, Ye Ding, Huamin Qu, Lionel Ni
Research Collection School Of Computing and Information Systems
Nowadays, big cities are suffering from severe traffic congestion as a result of the continuing increase in vehicles. Taxis equipped with GPS can be viewed as sensors of the traffic situation in city. However, trajectory data generated by taxi’s GPS traces are often high-dimensional and contain large spatial and temporal attributes, which pose challenges for analysts. In this paper, based on taxi trajectory data, we present an interactive visual analytics system, T-Watcher, for monitoring and analyzing complex traffic situations in big cities. Users are able to use a carefully designed interface to monitor and inspect data interactively from three levels …
Understanding Sequential Decisions Via Inverse Reinforcement Learning, Siyuan Liu, Miguel Araujo, Emma Brunskill, Rosaldo Rossetti, Joao Barros, Ramayya Krishnan
Understanding Sequential Decisions Via Inverse Reinforcement Learning, Siyuan Liu, Miguel Araujo, Emma Brunskill, Rosaldo Rossetti, Joao Barros, Ramayya Krishnan
Research Collection School Of Computing and Information Systems
The execution of an agent's complex activities, comprising sequences of simpler actions, sometimes leads to the clash of conflicting functions that must be optimized. These functions represent satisfaction, short-term as well as long-term objectives, costs and individual preferences. The way that these functions are weighted is usually unknown even to the decision maker. But if we were able to understand the individual motivations and compare such motivations among individuals, then we would be able to actively change the environment so as to increase satisfaction and/or improve performance. In this work, we approach the problem of providing highlevel and intelligible descriptions …
Improved Reachability Analysis In Dtmc Via Divide And Conquer, Songzheng Song, Lin Gui, Jun Sun, Yang Liu, Jin Song Dong
Improved Reachability Analysis In Dtmc Via Divide And Conquer, Songzheng Song, Lin Gui, Jun Sun, Yang Liu, Jin Song Dong
Research Collection School Of Computing and Information Systems
Discrete Time Markov Chains (DTMCs) are widely used to model probabilistic systems in many domains, such as biology, network and communication protocols. There are two main approaches for probability reachability analysis of DTMCs, i.e., solving linear equations or using value iteration. However, both approaches have drawbacks. On one hand, solving linear equations can generate accurate results, but it can be only applied to relatively small models. On the other hand, value iteration is more scalable, but often suffers from slow convergence. Furthermore, it is unclear how to parallelize (i.e., taking advantage of multi-cores or distributed computers) these two approaches. In …
A Formal Semantics For Complete Uml State Machines With Communications, Shuang Liu, Yang Liu, Étienne André, Christine Choppy, Jun Sun, Bimlesh Wadhwa, Jin Song Dong
A Formal Semantics For Complete Uml State Machines With Communications, Shuang Liu, Yang Liu, Étienne André, Christine Choppy, Jun Sun, Bimlesh Wadhwa, Jin Song Dong
Research Collection School Of Computing and Information Systems
UML is a widely used notation, and formalizing its semantics is an important issue. Here, we concentrate on formalizing UML state machines, used to express the dynamic behaviour of software systems. We propose a formal operational semantics covering all features of the latest version (2.4.1) of UML state machines specification. We use labelled transition systems as the semantic model, so as to use automatic verification techniques like model checking. Furthermore, our proposed semantics includes synchronous and asynchronous communications between state machines. We implement our approach in USM2C, a model checker supporting editing, simulation and automatic verification of UML state machines. …
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
No abstract provided.
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
No abstract provided.
Improving Internet Security Through Social Information And Social Comparison: A Field Quasi-Experiment, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew B. Whinston
Improving Internet Security Through Social Information And Social Comparison: A Field Quasi-Experiment, Qian Tang, Leigh L. Linden, John S. Quarterman, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
Cybersecurity is a national priority in this big data era. Because of negative externalities and the resulting lack of economic incentives, companies often underinvest in security controls, despite government and industry recommendations. Although many existing studies on security have explored technical solutions, only a few have looked at the economic motivations. To fill the gap, we propose an approach to increase the incentives of organizations to address security problems. Specifically, we utilize and process existing security vulnerability data, derive explicit security performance information, and disclose the information as feedback to organizations and the public. We regularly release information on the …
Mitigating Access-Driven Timing Channels In Clouds Using Stopwatch, Peng Li, Debin Gao, Michael K. Reiter
Mitigating Access-Driven Timing Channels In Clouds Using Stopwatch, Peng Li, Debin Gao, Michael K. Reiter
Research Collection School Of Computing and Information Systems
This paper presents StopWatch , a system that defends against timing-based side-channel attacks that arise from coresidency of victims and attackers in infrastructure-as-a-service clouds. StopWatchtriplicates each cloud-resident guest virtual machine (VM) and places replicas so that the three replicas of a guest VM are coresident with nonoverlapping sets of (replicas of) other VMs. StopWatch uses thetiming of I/O events at a VM's replicas collectively to determine the timings observed by each one or by an external observer, so that observable timing behaviors are similarly likely in the absence of any other individual, coresident VM. We detail the design and implementation …
When Do Consumers Purchase Online?: Based On Inter-Purchase Time, Youngsoo Kim
When Do Consumers Purchase Online?: Based On Inter-Purchase Time, Youngsoo Kim
Research Collection School Of Computing and Information Systems
This study is motivated by the premise that online consumers can make a purchase at any time of day if they have even a tiny time slot along with Internet access. To identify the increased shopping time flexibility, we first characterize the patterns of online purchase timing in comparison to those in the offline market. The results show (1) the breakdown of purchase timing regularity and (2) the change of weekly spike purchase occurrence. Second, we build online inter-purchase time model and estimate it with the data collected from one of the premier online vendors in Korea. We verify new …
Attribute-Based Access To Scalable Media In Cloud-Assisted Content Sharing, Yongdong Wu, Zhuo Wei, Robert H. Deng
Attribute-Based Access To Scalable Media In Cloud-Assisted Content Sharing, Yongdong Wu, Zhuo Wei, Robert H. Deng
Research Collection School Of Computing and Information Systems
This paper presents a novel Multi-message Ciphertext Policy Attribute-Based Encryption (MCP-ABE) technique, and employs the MCP-ABE to design an access control scheme for sharing scalable media based on data consumers’ attributes (e.g., age, nationality, gender) rather than an explicit list of the consumers’ names. The scheme is efficient and flexible because MCP-ABE allows a content provider to specify an access policy and encrypt multiple messages within one ciphertext such that only the users whose attributes satisfy the access policy can decrypt the ciphertext. Moreover, the paper shows how to support resource-limited mobile devices by offloading computational intensive perations to cloud …