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2018

Research Collection School Of Computing and Information Systems

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Full-Text Articles in Physical Sciences and Mathematics

Multi-Task Zipping Via Layer-Wise Neuron Sharing, Xiaoxi He, Zimu Zhou, Lothar Thiele Dec 2018

Multi-Task Zipping Via Layer-Wise Neuron Sharing, Xiaoxi He, Zimu Zhou, Lothar Thiele

Research Collection School Of Computing and Information Systems

Future mobile devices are anticipated to perceive, understand and react to the world on their own by running multiple correlated deep neural networks on-device. Yet the complexity of these neural networks needs to be trimmed down both within-model and cross-model to fit in mobile storage and memory. Previous studies squeeze the redundancy within a single model. In this work, we aim to reduce the redundancy across multiple models. We propose Multi-Task Zipping (MTZ), a framework to automatically merge correlated, pre-trained deep neural networks for cross-model compression. Central in MTZ is a layer-wise neuron sharing and incoming weight updating scheme that …

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Mobility-Driven Ble Transmit-Power Adaptation For Participatory Data Muling, Chung-Kyun Han, Archan Misra, Shih-Fen Cheng Dec 2018

Mobility-Driven Ble Transmit-Power Adaptation For Participatory Data Muling, Chung-Kyun Han, Archan Misra, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

This paper analyzes a human-centric framework, called SmartABLE, for easy retrieval of the sensor values from pervasively deployed smart objects in a campus-like environment. In this framework, smartphones carried by campus occupants act as data mules, opportunistically retrieving data from nearby BLE (Bluetooth Low Energy) equipped smart object sensors and relaying them to a backend repository. We focus specifically on dynamically varying the transmission power of the deployed BLE beacons, so as to extend their operational lifetime without sacrificing the frequency of sensor data retrieval. We propose a memetic algorithm-based power adaptation strategy that can handle deployments of thousands of …

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Credit Assignment For Collective Multiagent Rl With Global Rewards, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau Dec 2018

Credit Assignment For Collective Multiagent Rl With Global Rewards, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Scaling decision theoretic planning to large multiagent systems is challenging due to uncertainty and partial observability in the environment. We focus on a multiagent planning model subclass, relevant to urban settings, where agent interactions are dependent on their collective influence'' on each other, rather than their identities. Unlike previous work, we address a general setting where system reward is not decomposable among agents. We develop collective actor-critic RL approaches for this setting, and address the problem of multiagent credit assignment, and computing low variance policy gradient estimates that result in faster convergence to high quality solutions. We also develop difference …

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Perflearner: Learning From Bug Reports To Understand And Generate Performance Test Frames, Xue Han, Tingting Yu, David Lo Dec 2018

Perflearner: Learning From Bug Reports To Understand And Generate Performance Test Frames, Xue Han, Tingting Yu, David Lo

Research Collection School Of Computing and Information Systems

Software performance is important for ensuring the quality of software products. Performance bugs, defined as programming errors that cause significant performance degradation, can lead to slow systems and poor user experience. While there has been some research on automated performance testing such as test case generation, the main idea is to select workload values to increase the program execution times. These techniques often assume the initial test cases have the right combination of input parameters and focus on evolving values of certain input parameters. However, such an assumption may not hold for highly configurable real-word applications, in which the combinations …

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Applying Design Thinking To Student Outreach Projects: Experiences From An Information Systems School, Swapna Gottipati, Venky Shankararaman, Alan Megargel Dec 2018

Applying Design Thinking To Student Outreach Projects: Experiences From An Information Systems School, Swapna Gottipati, Venky Shankararaman, Alan Megargel

Research Collection School Of Computing and Information Systems

As countries turn into Smart Nations, Infocom Technology plays a key role in enhancing their competitiveness through high skilled workforces. Reaching to younger generations and attracting them to computing programs such as Information Systems (IS) and Computer Science (CS) is a key challenge faced by universities. Many high quality students from junior colleges either don’t choose IS programs or choose IS programs as their last option during the application process. A School of Information Systems (SIS) from a large metropolitan university decided to implement an innovative outreach program to attract high quality high school aka Junior College (JC) students. JC …

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Privacy-Preserving Remote User Authentication With K-Times Untraceability, Yangguang Tian, Yingjiu Li, Binanda Sengupta, Robert H. Deng, Albert Ching, Weiwei Liu Dec 2018

Privacy-Preserving Remote User Authentication With K-Times Untraceability, Yangguang Tian, Yingjiu Li, Binanda Sengupta, Robert H. Deng, Albert Ching, Weiwei Liu

Research Collection School Of Computing and Information Systems

Remote user authentication has found numerous real-world applications, especially in a user-server model. In this work, we introduce the notion of anonymous remote user authentication with k-times untraceability (k-RUA) for a given parameter k, where authorized users authenticate themselves to an authority (typically a server) in an anonymous and k-times untraceable manner. We define the formal security models for a generic k-RUA construction that guarantees user authenticity, anonymity and user privacy. We provide a concrete instantiation of k-RUA having the following properties: (1) a third party cannot impersonate an authorized user by producing valid transcripts for the user while conversing …

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Sybmatch: Sybil Detection For Privacy-Preserving Task Matching In Crowdsourcing, Jiangang Shu, Ximeng Liu, Kan Yang, Yinghui Zhang, Xiaohua Jia, Robert H. Deng Dec 2018

Sybmatch: Sybil Detection For Privacy-Preserving Task Matching In Crowdsourcing, Jiangang Shu, Ximeng Liu, Kan Yang, Yinghui Zhang, Xiaohua Jia, Robert H. Deng

Research Collection School Of Computing and Information Systems

The past decade has witnessed the rise of crowdsourcing, and privacy in crowdsourcing has also gained rising concern in the meantime. In this paper, we focus on the privacy leaks and sybil attacks during the task matching, and propose a privacy-preserving task matching scheme, called SybMatch. The SybMatch scheme can simultaneously protect the privacy of publishers and subscribers against semi-honest crowdsourcing service provider, and meanwhile support the sybil detection against greedy subscribers and efficient user revocation. Detailed security analysis and thorough performance evaluation show that the SybMatch scheme is secure and efficient.

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Making A Good Thing Better: Enhancing Password/Pin-Based User Authentication With Smartwatch, Bing Chang, Yingjiu Li, Qiongxiao Wang, Wen-Tao Zhu, Robert H. Deng Dec 2018

Making A Good Thing Better: Enhancing Password/Pin-Based User Authentication With Smartwatch, Bing Chang, Yingjiu Li, Qiongxiao Wang, Wen-Tao Zhu, Robert H. Deng

Research Collection School Of Computing and Information Systems

Wearing smartwatches becomes increasingly popular in people’s lives. This paper shows that a smartwatch can help its bearer authenticate to a login system effectively and securely even if the bearer’s password has already been revealed. This idea is motivated by our observation that a sensor-rich smartwatch is capable of tracking the wrist motions of its bearer typing a password or PIN, which can be used as an authentication factor. The major challenge in this research is that a sophisticated attacker may imitate a user’s typing behavior as shown in previous research on keystroke dynamics based user authentication. We address this …

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Utilizing Computational Trust To Identify Rumor Spreaders On Twitter, Bhavtosh Rath, Wei Gao, Jing Ma, Jaideep Srivastava Dec 2018

Utilizing Computational Trust To Identify Rumor Spreaders On Twitter, Bhavtosh Rath, Wei Gao, Jing Ma, Jaideep Srivastava

Research Collection School Of Computing and Information Systems

Ubiquitous use of social media such as microblogging platforms opens unprecedented chances for false information to diffuse online. Facing the challenges in such a so-called “post-fact” era, it is very important for intelligent systems to not only check the veracity of information but also verify the authenticity of the users who spread the information, especially in time-critical situations such as real-world emergencies, where urgent measures have to be taken for stopping the spread of fake information. In this work, we propose a novel machine-learning-based approach for automatic identification of the users who spread rumorous information on Twitter by leveraging computational …

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Automatically `Verifying’ Discrete-Time Complex Systems Through Learning, Abstraction And Refinement, Jingyi Wang, Jun Sun, Shengchao Qin, Cyrille Jegourel Dec 2018

Automatically `Verifying’ Discrete-Time Complex Systems Through Learning, Abstraction And Refinement, Jingyi Wang, Jun Sun, Shengchao Qin, Cyrille Jegourel

Research Collection School Of Computing and Information Systems

Precisely modeling complex systems like cyber-physical systems is challenging, which often render model-based system verification techniques like model checking infeasible. To overcome this challenge, we propose a method called LAR to automatically ‘verify’ such complex systems through a combination of learning, abstraction and refinement from a set of system log traces. We assume that log traces and sampling frequency are adequate to capture ‘enough’ behaviour of the system. Given a safety property and the concrete system log traces as input, LAR automatically learns and refines system models, and produces two kinds of outputs. One is a counterexample with a bounded …

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Co-Location Resistant Virtual Machine Placement In Cloud Data Centers, Amit Agarwal, Nguyen Binh Duong Ta Dec 2018

Co-Location Resistant Virtual Machine Placement In Cloud Data Centers, Amit Agarwal, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

Due to increasing number of avenues for conducting cross-virtual machine (VM) side-channel attacks, the security of public IaaS cloud data centers is a growing concern. These attacks allow an adversary to steal private information from a target user whose VM instance is co-located with that of the adversary. To reduce the probability of malicious co-location, we propose a novel VM placement algorithm called “Previously Co-Located Users First”. We perform a theoretical and empirical analysis of our proposed algorithm to evaluate its resource efficiency and security. Our results, obtained using real-world cloud traces containing millions of VM requests and thousands of …

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Deep Air Learning: Interpolation, Prediction, And Feature Analysis Of Fine-Grained Air Quality, Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, Zhongfei Mark Zhang Dec 2018

Deep Air Learning: Interpolation, Prediction, And Feature Analysis Of Fine-Grained Air Quality, Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, Zhongfei Mark Zhang

Research Collection School Of Computing and Information Systems

The interpolation, prediction, and feature analysis of fine-gained air quality are three important topics in the area of urban air computing. The solutions to these topics can provide extremely useful information to support air pollution control, and consequently generate great societal and technical impacts. Most of the existing work solves the three problems separately by different models. In this paper, we propose a general and effective approach to solve the three problems in one model called the Deep Air Learning (DAL). The main idea of DAL lies in embedding feature selection and semi-supervised learning in different layers of the deep …

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Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li Dec 2018

Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Modern Code Review (MCR) has been widely used by open source and proprietary software projects. Inspecting code changes consumes reviewers much time and effort since they need to comprehend patches, and many reviewers are often assigned to review many code changes. Note that a code change might be eventually abandoned, which causes waste of time and effort. Thus, a tool that predicts early on whether a code change will be merged can help developers prioritize changes to inspect, accomplish more things given tight schedule, and not waste reviewing effort on low quality changes. In this paper, motivated by the above …

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Effectiveness Of Physical Robot Versus Robot Simulator In Teaching Introductory Programming, Oka Kurniawan, Norman Tiong Seng Lee, Subhajit Datta, Nachamma Sockalingam, Pey Lin Leong Dec 2018

Effectiveness Of Physical Robot Versus Robot Simulator In Teaching Introductory Programming, Oka Kurniawan, Norman Tiong Seng Lee, Subhajit Datta, Nachamma Sockalingam, Pey Lin Leong

Research Collection School Of Computing and Information Systems

This study reports the use of a physical robot and robot simulator in an introductory programming course in a university and measures students' programming background conceptual learning gain and learning experience. One group used physical robots in their lessons to complete programming assignments, while the other group used robot simulators. We are interested in finding out if there is any difference in the learning gain and experiences between those that use physical robots as compared to robot simulators. Our results suggest that there is no significant difference in terms of students' learning between the two approaches. However, the control group …

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Data Center Holistic Demand Response Algorithm To Smooth Microgrid Tie-Line Power Fluctuation, Ting Yang, Yingjie Zhao, Haibo Pen, Zhaoxia Wang Dec 2018

Data Center Holistic Demand Response Algorithm To Smooth Microgrid Tie-Line Power Fluctuation, Ting Yang, Yingjie Zhao, Haibo Pen, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

With the rapid development of cloud computing, artificial intelligence technologies and big data applications, data centers have become widely deployed. High density IT equipment in data centers consumes a lot of electrical power, and makes data center a hungry monster of energy consumption. To solve this problem, renewable energy is increasingly integrated into data center power provisioning systems. Compared to the traditional power supply methods, renewable energy has its unique characteristics, such as intermittency and randomness. When renewable energy supplies power to the data center industrial park, this kind of power supply not only has negative effects on the normal …

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Text Analytics Approach To Extract Course Improvement Suggestions From Students’ Feedback, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin Dec 2018

Text Analytics Approach To Extract Course Improvement Suggestions From Students’ Feedback, Swapna Gottipati, Venky Shankararaman, Jeff Rongsheng Lin

Research Collection School Of Computing and Information Systems

In academic institutions, it is normal practice that at the end of each term, students are required to complete a questionnaire that is designed to gather students’ perceptions of the instructor and their learning experience in the course. Students’ feedback includes numerical answers to Likert scale questions and textual comments to open-ended questions. Within the textual comments given by the students are embedded suggestions. A suggestion can be explicit or implicit. Any suggestion provides useful pointers on how the instructor can further enhance the student learning experience. However, it is tedious to manually go through all the qualitative comments and …

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An Essential Applied Statistical Analysis Course Using Rstudio With Project-Based Learning For Data Science, Aldy Gunawan, Michelle L. F. Cheong, Johnson Poh Dec 2018

An Essential Applied Statistical Analysis Course Using Rstudio With Project-Based Learning For Data Science, Aldy Gunawan, Michelle L. F. Cheong, Johnson Poh

Research Collection School Of Computing and Information Systems

This paper presents a newpostgraduate level course, named Applied Statistical Analysis with R. Wepresent the course structure, teaching methodology including the assessmentframework and student feedback. The course covers the basic concepts ofstatistics, the knowledge of applying statistical theory in analyzing real dataand the skill of developing statistical applications with R programminglanguage. The first half of each lesson is dedicated to teaching students thestatistical concepts while the second half focuses on the practical aspects ofimplementing the concepts within the RStudio console. The Project-BasedLearning (PBL) approach is adopted to encourage students to apply the knowledgegained to solve real world problems, answer complex …

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Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, Quang Tran Minh, Chanh Minh Tran, Tuan An Le, Binh Thai Nguyen, Triet Minh Tran, Rajesh Krishna Balan Dec 2018

Fogfly: A Traffic Light Optimization Solution Based On Fog Computing, Quang Tran Minh, Chanh Minh Tran, Tuan An Le, Binh Thai Nguyen, Triet Minh Tran, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

This paper provides a fog-based approach to solving the traffic light optimization problem which utilizes the Adaptive Traffic Signal Control (ATSC) model. ATSC systems demand the ability to strictly reflect real-time traffic state. The proposed fog computing framework, namely FogFly, aligns with this requirement by its natures in location-awareness, low latency and affordability to the changes in traffic conditions. As traffic data is updated timely and processed at fog nodes deployed close to data sources (i.e., vehicles at intersections) traffic light cycles can be optimized efficiently while virtualized resources available at network edges are efficiently utilized. Evaluation results show that …

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Data Mining Approach To The Identification Of At-Risk Students, Li Chin Ho, Kyong Jin Shim Dec 2018

Data Mining Approach To The Identification Of At-Risk Students, Li Chin Ho, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

In recent years, the use of digital tools and technologies in educational institutions are continuing to generate large amounts of digital traces of student learning behavior. This study presents a proof-of-concept analytics system that can detect at-risk students along their learning journey. Educators can benefit from the early detection of at-risk students by understanding factors which may lead to failure or drop-out. Further, educators can devise appropriate intervention measures before the students drop out of the course. Our system was built using SAS ® Enterprise Miner (EM) and SAS ® JMP Pro.

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Data Mining Approach To The Detection Of Suicide In Social Media: A Case Study Of Singapore, Jane H. K. Seah, Kyong Jin Shim Dec 2018

Data Mining Approach To The Detection Of Suicide In Social Media: A Case Study Of Singapore, Jane H. K. Seah, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

In this research, we focus on the social phenomenon of suicide. Specifically, we perform social sensing on digital traces obtained from Reddit. We analyze the posts and comments in that are related to depression and suicide. We perform natural language processing to better understand different aspects of human life that relate to suicide.

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An Architectural Design And Evaluation Of An Affective Tutoring System For Novice Programmers, Hua Leong Fwa Dec 2018

An Architectural Design And Evaluation Of An Affective Tutoring System For Novice Programmers, Hua Leong Fwa

Research Collection School Of Computing and Information Systems

Affect is prevalent in learning and it influences students’ learning achievement. This paper details the design and evaluation of an Affective Tutoring System (ATS) that tutors student in computer programming. Although most ATSs are purpose built for a specific domain, making adaptation to another domain difficult, this ATS is architected for adaptability and extensibility. This study also addresses a lack of research exploring the theories and methods of integrating affect and learning within the learning process by proposing methods of regulating the negative affect of students. Both quantitative and qualitative techniques were used for evaluation of the effectiveness of the …

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A Simple Proximal Stochastic Gradient Method For Nonsmooth Nonconvex Optimization, Zhize Li, Jian Li Dec 2018

A Simple Proximal Stochastic Gradient Method For Nonsmooth Nonconvex Optimization, Zhize Li, Jian Li

Research Collection School Of Computing and Information Systems

We analyze stochastic gradient algorithms for optimizing nonconvex, nonsmooth finite-sum problems. In particular, the objective function is given by the summation of a differentiable (possibly nonconvex) component, together with a possibly non-differentiable but convex component. We propose a proximal stochastic gradient algorithm based on variance reduction, called ProxSVRG+. Our main contribution lies in the analysis of ProxSVRG+. It recovers several existing convergence results and improves/generalizes them (in terms of the number of stochastic gradient oracle calls and proximal oracle calls). In particular, ProxSVRG+ generalizes the best results given by the SCSG algorithm, recently proposed by [Lei et al., NIPS'17] for …

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Authorized Function Homomorphic Signature, Qingwen Guo, Qiong Huang, Guomin Yang Dec 2018

Authorized Function Homomorphic Signature, Qingwen Guo, Qiong Huang, Guomin Yang

Research Collection School Of Computing and Information Systems

Homomorphic signature (HS) is a novel primitive that allows an agency to carry out arbitrary (polynomial time) computation f on the signed data (m) over right arrow and accordingly gain a signature sigma(h) for the computation result f ((m) over right arrow) with respect to f on behalf of the data owner (DO). However, since DO lacks control of the agency's behavior, receivers would believe that DO did authenticate the computation result even if the agency misbehaves and applies a function that the DO does not want. To address the problem above, in this paper we introduce a new primitive …

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Active Matting, Xin Yang, Ke Xu, Shaozhe Chen, Shengfeng He, Baocai Yin, Rynson Lau Dec 2018

Active Matting, Xin Yang, Ke Xu, Shaozhe Chen, Shengfeng He, Baocai Yin, Rynson Lau

Research Collection School Of Computing and Information Systems

Image matting is an ill-posed problem. It requires a user input trimap or some strokes to obtain an alpha matte of the foreground object. A fine user input is essential to obtain a good result, which is either time consuming or suitable for experienced users who know where to place the strokes. In this paper, we explore the intrinsic relationship between the user input and the matting algorithm to address the problem of where and when the user should provide the input. Our aim is to discover the most informative sequence of regions for user input in order to produce …

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The Living Wall Display: Physical Augmentation Of Interactive Content Using An Autonomous Mobile Display, Yuki Onishi, Yoshiki Kudo, Kazuki Takashima, Anthony Tang, Yoshifumi Kitamura Dec 2018

The Living Wall Display: Physical Augmentation Of Interactive Content Using An Autonomous Mobile Display, Yuki Onishi, Yoshiki Kudo, Kazuki Takashima, Anthony Tang, Yoshifumi Kitamura

Research Collection School Of Computing and Information Systems

The Living Wall Display displays interactive content on a mobile wall screen that moves in concert with content animation. To augment the interaction experience, the display dynamically changes its position and orientation, responding to the content animation triggered by user interactions. We implement three proof of concept prototypes that represent pseudo force impact of the interactive content using physical screen movement. Pilot studies show that the Living Wall augments content expressiveness, and increases the sense of presence of the screen content.

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Typing-Proof: Usable, Secure And Low-Cost Two-Factor Authentication Based On Keystroke Timings, Ximming Liu, Yingjiu Li, Robert H. Deng Dec 2018

Typing-Proof: Usable, Secure And Low-Cost Two-Factor Authentication Based On Keystroke Timings, Ximming Liu, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Two-factor authentication (2FA) systems provide another layer of protection to users' accounts beyond password. Traditional hardware token based 2FA and software token based 2FA are not burdenless to users since they require users to read, remember, and type a onetime code in the process, and incur high costs in deployments or operations. Recent 2FA mechanisms such as Sound-Proof, reduce or eliminate users' interactions for the proof of the second factor; however, they are not designed to be used in certain settings (e.g., quiet environments or PCs without built-in microphones), and they are not secure in the presence of certain attacks …

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On Learning Psycholinguistics Tools For English-Based Creole Languages Using Social Media Data, Pei-Chi Lo, Ee-Peng Lim Dec 2018

On Learning Psycholinguistics Tools For English-Based Creole Languages Using Social Media Data, Pei-Chi Lo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

The Linguistic Inquiry and Word Count (LIWC) tool is a psycholinguistics tool that has been widely used in both psychology and sociology research, and the LIWC scores derived from user-generated content are known to be good features for personality prediction [1], [2]. LIWC, however, is language specific as it relies on counting the percentage of predefined dictionary words occurring in the content. For content written in English Creoles which are languages based on English, the original English LIWC may not perform optimally due to its lack of words which are only used in the English Creoles. In this paper, we …

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Vr Safari Park: A Concept-Based World Building Interface Using Blocks And World Tree, Shotaro Ichikawa, Anthony Tang, Kazuki Takashima, Yoshifumi Kitamura Dec 2018

Vr Safari Park: A Concept-Based World Building Interface Using Blocks And World Tree, Shotaro Ichikawa, Anthony Tang, Kazuki Takashima, Yoshifumi Kitamura

Research Collection School Of Computing and Information Systems

We present a concept-based world building approach, realized in a system called VR Safari Park, which allows users to rapidly create and manipulate a world simulation. Conventional world building tools focus on the manipulation and arrangement of entities to set up the simulation, which is time consuming as it requires frequent view and entity manipulations. Our approach focuses on a far simpler mechanic, where users add virtual blocks which represent world entities (e.g. animals, terrain, weather, etc.) to a World Tree, which represents the simulation. In so doing, the World Tree provides a quick overview of the simulation, and users …

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Deep Unsupervised Pixelization, Chu Han, Qiang Wen, Shengfeng He, Qianshu Zhu, Yinjie Tan, Guoqiang Han, Tien-Tsin Wong Dec 2018

Deep Unsupervised Pixelization, Chu Han, Qiang Wen, Shengfeng He, Qianshu Zhu, Yinjie Tan, Guoqiang Han, Tien-Tsin Wong

Research Collection School Of Computing and Information Systems

In this paper, we present a novel unsupervised learning method for pixelization. Due to the difficulty in creating pixel art, preparing the paired training data for supervised learning is impractical. Instead, we propose an unsupervised learning framework to circumvent such difficulty. We leverage the dual nature of the pixelization and depixelization, and model these two tasks in the same network in a bi-directional manner with the input itself as training supervision. These two tasks are modeled as a cascaded network which consists of three stages for different purposes. GridNet transfers the input image into multi-scale grid-structured images with different aliasing …

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Secure Smart Health With Privacy-Aware Aggregate Authentication And Access Control In Internet Of Things, Yinghui Zhang, Robert H. Deng, Gang Han, Dong Zheng Dec 2018

Secure Smart Health With Privacy-Aware Aggregate Authentication And Access Control In Internet Of Things, Yinghui Zhang, Robert H. Deng, Gang Han, Dong Zheng

Research Collection School Of Computing and Information Systems

With the rapid technological advancements in the Internet of Things (IoT), wireless communication and cloud computing, smart health is expected to enable comprehensive and qualified healthcare services. It is important to ensure security and efficiency in smart health. However, existing smart health systems still have challenging issues, such as aggregate authentication, fine-grained access control and privacy protection. In this paper, we address these issues by introducing SSH, a Secure Smart Health system with privacy-aware aggregate authentication and access control in IoT. In SSH, privacy-aware aggregate authentication is enabled by an anonymous certificateless aggregate signature scheme, in which users' identity information …

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