Privacy-preserving fusion of IoT and big data for e-health

Yang, Yang; Zheng, Xianghan; Guo, Wenzhong; Liu, Ximeng; Chang, Victor

doi:10.1016/j.future.2018.01.003

Cited by 109 publications

(56 citation statements)

References 34 publications

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“…A privacy preserving anonymity and traceability patient's data medical node of an IoT is proposed in [7]. The privacy of the patients are preserved using attribute based encryption technique (ABE).…”

Section: A Anonymization Techniques On Iotmentioning

confidence: 99%

Privacy-Preserving Internet of Things: Techniques and Applications

J*¹,

Karthikeyan²

2019

IJEAT

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Abstract: Privacy has become an imperative term in the recent technology developments. Lots of data are being collected through every digital activity of users. The expeditious development of IoT applications have raised the concern about the privacy of the IoT systems. The data collected via IoT sensors can reveal the daily behavior of the users, location, and other sensitive information. Hence, it is necessary to preserve the privacy of data collected by IoT devices. A large number of techniques and approaches have been implemented and used in different IoT based applications such as cloud computing based IoT, fog computing based IoT, blockchain based IoT and trajectory applications. In this paper, we present a detailed investigation of the existing approaches to preserve the privacy of data in IoT applications. The techniques like k-anonymity, secure multiparty computation, attribute based encryption and homomorphic encryption are analyzed. Finally, a comparative analysis of privacy preserving techniques with its applications are presented.

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Section: A Anonymization Techniques On Iotmentioning

confidence: 99%

Privacy-Preserving Internet of Things: Techniques and Applications

J*¹,

Karthikeyan²

2019

IJEAT

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“…Mai introduces the privacy datafication model that the analysis of already available data enables others to generate new insights through (Mai, 2015;Pham et al, 2016) propose a privacy-enhanced service called "PrivateRide" including four cryptographic tools, it can protect passengers' anonymity and location privacy, while maintaining most of the benefits of current service providers. (Yang et al, 2018) take the big data technology and design a keyword match based on updating mechanism, which runs the updating as well as ensuring the privacy security. (Banerjee et al, 2017) highlight the government's responsibility in identification, monitoring and examination the data to solve privacy issue.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The scholars design a keyword match based on updating mechanism, which can make the updating as well as ensuring the privacy security (Yang et al, 2018).…”

Section: The Recommendations To Privacy Issuementioning

confidence: 99%

Contemporary Issues in the Ethics of Data Analytics in Ride-Hailing Service

Chang

Shi

2019

International Journal of Strategic Engineering

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Big data technology has brought about the establishment of transportation network companies (TNCs), such as Uber in the USA, and Didi in China, who provide the ride hailing services (RHS's) which allows the individuals to act as independent contractors serving customers via a smartphone app. The RHS system installed gigantic databases which can store enormous data and its equipment can collect various kinds of data at any time. Additionally, data analysis technologies in TNCs such as behavioral analysis, heatmap optimization surge pricing and the automatic order assignment mechanisms, can make the RHS more efficient. However, along with achievements big data technology offers, we are struggling towards the ethical problems, including privacy, inequity and safety.

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“…Over the few last decade, the data growth from Internet of Things (IoT), multimedia, and different sensing devices introduce a huge amount of data in unstructured, semi structured or structured format called big data [8]. IoT brings weighty advantages over traditional communication technologies in Healthcare sector [9]. IoT based medical file cloud storage system which control and secure deduplication and also provide facility to manage the data in EHS [10].…”

Section: Introductionmentioning

confidence: 99%

From cloud computing to fog computing in Healthcare big data

et al. 2018

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In Healthcare big data, data is originated from various heterogeneous sources. Numerous novel base particular healthcare applications offered to handling source of data from electronic health record (EHR) to medical images. Imaging, Electronic Health Report, technology in light of sensor and numerous different procedures created an immense measure of Healthcare data. Cloud computing development was an excellent paradigm to substantiate big data which incited find of imperceptible examples. Cloud computing is a developing new registering design intended to answer different contending administrations on the Web. Fog Computing is a design style in which arrange segments amongst devices and the cloud execute application-particular rationale. We in this paper investigate, characterize, and talk about various application of cloud and fog computing. We talk about the impact of cloud computing and fog computing on healthcare big data. Cloud base framework for Homediagnosis Service, Fog computing architecture and the justification of moving from cloud to Fog presented comprehensively in this paper.

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Privacy-preserving fusion of IoT and big data for e-health

Cited by 109 publications

References 34 publications

Privacy-Preserving Internet of Things: Techniques and Applications

Privacy-Preserving Internet of Things: Techniques and Applications

Contemporary Issues in the Ethics of Data Analytics in Ride-Hailing Service

From cloud computing to fog computing in Healthcare big data

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