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Full-Text Articles in Physical Sciences and Mathematics

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 …


Better Inpatient Health Quality At Lower Cost: Should I Participate In The Online Healthcare Community First?, Kai Luo, Qiu-Hong Wang, Hock Hai Teo, Xi Chen Dec 2018

Better Inpatient Health Quality At Lower Cost: Should I Participate In The Online Healthcare Community First?, Kai Luo, Qiu-Hong Wang, Hock Hai Teo, Xi Chen

Research Collection School Of Computing and Information Systems

As policy makers across the globe look to health information technology (HIT) as a meansof improving the efficiency of the healthcare systems, it has sparked significant interestin understanding how HIT might help achieve that. While researchers have examined anddocumented the efficiency-improving effect of various institution HITs (e.g., electronicclinic pathways and telemedicine), the impacts of consumer HITs such as onlinehealthcare communities have been generally overlooked. Utilizing two unique datasetsfrom both an online healthcare community and a general hospital, we study the impactof online healthcare community on offline inpatient care efficiency. Through rigorousanalysis, we find that communications between physicians and patients on …


Lightweight Break-Glass Access Control System For Healthcare Internet-Of-Things, Yang Yang, Ximeng Liu, Robert H. Deng Aug 2018

Lightweight Break-Glass Access Control System For Healthcare Internet-Of-Things, Yang Yang, Ximeng Liu, Robert H. Deng

Research Collection School Of Computing and Information Systems

Healthcare Internet-of-things (IoT) has been proposed as a promising means to greatly improve the efficiency and quality of patient care. Medical devices in healthcare IoT measure patients' vital signs and aggregate these data into medical files which are uploaded to the cloud for storage and accessed by healthcare workers. To protect patients' privacy, encryption is normally used to enforce access control of medical files by authorized parties while preventing unauthorized access. In healthcare, it is crucial to enable timely access of patient files in emergency situations. In this paper, we propose a lightweight break-glass access control (LiBAC) system that supports …


Disease Gene Classification With Metagraph Representations, Sezin Kircali Ata, Yuan Fang, Min Wu, Xiao-Li Li, Xiaokui Xiao Jul 2018

Disease Gene Classification With Metagraph Representations, Sezin Kircali Ata, Yuan Fang, Min Wu, Xiao-Li Li, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

This chapter is based on exploiting the network-based representations of proteins, metagraphs, in protein-protein interaction network to identify candidate disease-causing proteins. Protein-protein interaction (PPI) networks are effective tools in studying the functional roles of proteins in the development of various diseases. However, they are insufficient without the support of additional biological knowledge for proteins such as their molecular functions and biological processes. To enhance PPI networks, we utilize biological properties of individual proteins as well. More specifically, we integrate keywords from UniProt database describing protein properties into the PPI network and construct a novel heterogeneous PPI-Keyword (PPIK) network consisting …


Detecting Personal Intake Of Medicine From Twitter, Debanjan Mahata, Jasper Friedrichs, Rajiv Ratn Shah, Jing Jiang Jul 2018

Detecting Personal Intake Of Medicine From Twitter, Debanjan Mahata, Jasper Friedrichs, Rajiv Ratn Shah, Jing Jiang

Research Collection School Of Computing and Information Systems

Mining social media messages such as tweets, blogs, and Facebook posts for health and drug related information has received significant interest in pharmacovigilance research. Social media sites (e.g., Twitter), have been used for monitoring drug abuse, adverse reactions to drug usage, and analyzing expression of sentiments related to drugs. Most of these studies are based on aggregated results from a large population rather than specific sets of individuals. In order to conduct studies at an individual level or specific groups of people, identifying posts mentioning intake of medicine by the user is necessary. Toward this objective we develop a classifier …


Security And Privacy In Smart Health: Efficient Policy-Hiding Attribute-Based Access Control, Yinghui Zhang, Dong Zheng, Robert H. Deng Jun 2018

Security And Privacy In Smart Health: Efficient Policy-Hiding Attribute-Based Access Control, Yinghui Zhang, Dong Zheng, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the rapid development of the Internet of Things (IoT) and cloud computing technologies, smart health (s-health) is expected to significantly improve the quality of health care. However, data security and user privacy concerns in s-health have not been adequately addressed. As a well-received solution to realize fine-grained access control, ciphertext-policy attribute-based encryption (CP-ABE) has the potential to ensure data security in s-health. Nevertheless, direct adoption of the traditional CP-ABE in s-health suffers two flaws. For one thing, access policies are in cleartext form and reveal sensitive health-related information in the encrypted s-health records (SHRs). For another, it usually supports …


Finding Small-Bowel Lesions: Challenges In Endoscopy-Image-Based Learning Systems, Jungmo Ahn, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee, Jeonggil Ko May 2018

Finding Small-Bowel Lesions: Challenges In Endoscopy-Image-Based Learning Systems, Jungmo Ahn, Loc Nguyen Huynh, Rajesh Krishna Balan, Youngki Lee, Jeonggil Ko

Research Collection School Of Computing and Information Systems

Capsule endoscopy identifies damaged areas in a patient's small intestine but often outputs poor-quality images or misses lesions, leading to either misdiagnosis or repetition of the lengthy procedure. The authors propose applying deep-learning models to automatically process the captured images and identify lesions in real time, enabling the capsule to take additional images of a specific location, adjust its focus level, or improve image quality. The authors also describe the technical challenges in realizing a viable automated capsule-endoscopy system.


Does Journaling Encourage Healthier Choices? Analyzing Healthy Eating Behaviors Of Food Journalers, Palakorn Achananuparp, Ee Peng Lim, Vibhanshu Abhishek Apr 2018

Does Journaling Encourage Healthier Choices? Analyzing Healthy Eating Behaviors Of Food Journalers, Palakorn Achananuparp, Ee Peng Lim, Vibhanshu Abhishek

Research Collection School Of Computing and Information Systems

Past research has shown the benefits of food journaling in promoting mindful eating and healthier food choices. However, the links between journaling and healthy eating have not been thoroughly examined. Beyond caloric restriction, do journalers consistently and sufficiently consume healthful diets? How different are their eating habits compared to those of average consumers who tend to be less conscious about health? In this study, we analyze the healthy eating behaviors of active food journalers using data from MyFitnessPal. Surprisingly, our findings show that food journalers do not eat as healthily as they should despite their proclivity to health eating and …


Eat & Tell: A Randomized Trial Of Random-Loss Incentive To Increase Dietary Self-Tracking Compliance, Palakorn Achananuparp, Ee Peng Lim, Vibhanshu Abhishek, Tianjiao Yun Apr 2018

Eat & Tell: A Randomized Trial Of Random-Loss Incentive To Increase Dietary Self-Tracking Compliance, Palakorn Achananuparp, Ee Peng Lim, Vibhanshu Abhishek, Tianjiao Yun

Research Collection School Of Computing and Information Systems

A growing body of evidence has shown that incorporating behavioral economics principles into the design of financial incentive programs helps improve their cost-effectiveness, promote individuals' short-term engagement, and increase compliance in health behavior interventions. Yet, their effects on long-term engagement have not been fully examined. In study designs where repeated administration of incentives is required to ensure the regularity of behaviors, the effectiveness of subsequent incentives may decrease as a result of the law of diminishing marginal utility. In this paper, we introduce random-loss incentive-a new financial incentive based on loss aversion and unpredictability principles-to address the problem of individuals' …


Fast And Robust Segmentation Of White Blood Cell Images By Self-Supervised Learning, Xin Zheng, Yong Wang, Guoyou Wang, Jianguo Liu Apr 2018

Fast And Robust Segmentation Of White Blood Cell Images By Self-Supervised Learning, Xin Zheng, Yong Wang, Guoyou Wang, Jianguo Liu

Research Collection School Of Computing and Information Systems

A fast and accurate white blood cell (WBC) segmentation remains a challenging task, as different WBCs vary significantly in color and shape due to cell type differences, staining technique variations and the adhesion between the WBC and red blood cells. In this paper, a self-supervised learning approach, consisting of unsupervised initial segmentation and supervised segmentation refinement, is presented. The first module extracts the overall foreground region from the cell image by K-means clustering, and then generates a coarse WBC region by touching-cell splitting based on concavity analysis. The second module further uses the coarse segmentation result of the first module …


Dispatch Guided Allocation Optimization For Effective Emergency Response, Supriyo Ghosh, Pradeep Varakantham Feb 2018

Dispatch Guided Allocation Optimization For Effective Emergency Response, Supriyo Ghosh, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Effective emergency (medical, fire or criminal) response iscrucial for improving safety and security in urban environments. Recent research in improving effectiveness of emergency management systems (EMSs) has utilized data-drivenoptimization models for efficient allocation of emergency response vehicles (ERVs) to base locations. However, thesedata-driven optimization models either ignore the dispatchstrategy of ERVs (typically the nearest available ERV is dispatched to serve an incident) or employ myopic approaches(e.g., greedy approach based on marginal gain). This resultsin allocations that are not synchronised with the real evolution dynamics on the ground or can be improved significantly.To bridge this gap, we make the following contributions: …


Hybrid Privacy-Preserving Clinical Decision Support System In Fog-Cloud Computing, Ximeng Liu, Robert H. Deng, Yang Yang, Ngoc Hieu Tran, Shangping Zhong Jan 2018

Hybrid Privacy-Preserving Clinical Decision Support System In Fog-Cloud Computing, Ximeng Liu, Robert H. Deng, Yang Yang, Ngoc Hieu Tran, Shangping Zhong

Research Collection School Of Computing and Information Systems

In this paper, we propose a framework for hybrid privacy-preserving clinical decision support system in fog cloud computing, called HPCS. In HPCS, a fog server uses a lightweight data mining method to securely monitor patients' health condition in real-time. The newly detected abnormal symptoms can be further sent to the cloud server for high-accuracy prediction in a privacy-preserving way. Specifically, for the fog servers, we design a new secure outsourced inner-product protocol for achieving secure lightweight single-layer neural network. Also, a privacy-preserving piecewise polynomial calculation protocol allows cloud server to securely perform any activation functions in multiple-layer neural network. Moreover, …


A Lightweight Policy Preserving Ehr Sharing Scheme In The Cloud, Zuobin Ying, Lu Wei, Qi Li, Ximeng Liu, Jie Cui Jan 2018

A Lightweight Policy Preserving Ehr Sharing Scheme In The Cloud, Zuobin Ying, Lu Wei, Qi Li, Ximeng Liu, Jie Cui

Research Collection School Of Computing and Information Systems

Electronic Health Record (EHR) is a digital health documentary. It contains not only the health-related records but also the personal sensitive information. Therefore, how to reliably share EHR through the cloud is a challenging issue. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptography prototype, which can achieve fine-grained access control as well as one-to-many encryption. In CP-ABE, access policy is attached to the ciphertext, and however, the access policy is not protected, which will also cause some privacy leakage. In this paper, we propose a policy preserving EHR system on the basis of CP-ABE. Specifically, we designed an algorithm, which …