scholarly journals Balancing Privacy Vs Efficiency in Data Analytics using Nearest Neighbour Randomization

2019 ◽  
Vol 8 (12) ◽  
pp. 2289-2295
Keyword(s):  
Data Analytics ◽  
Large Scale ◽  
Personal Data ◽  
Privacy And Security ◽  
Computing Platform ◽  
Use Of Data ◽  
Digital Era ◽  
Considerable Research ◽  
Group Data ◽  
Security Practices

The Digital era marked by the unrivalled growth of Internet and its services with day-to-day technological advancements has paved way for a data driven society. This digital explosion offers opportunities for extracting valuable information from collected data, which are used by organizations and research establishments for synergistic advantage. However, privacy of online divulged data is an issue that gets overlooked as a consequence of such large-scale analytics. Although, privacy and security practices conjointly determine the ethics of data collection and its use, personal data of individuals is largely at risk of disclosure. Considerable research has gone into privacy preserving analytics, in the light of Big Data and IoT boom, but scalable and efficient techniques, that do not compromise the usefulness of privacy constrained data, continues to be a challenging arena for research. The proposed work makes use of a distance-based perturbation method to group data and further randomizes data. The efficacy of perturbed data is evaluated for classification task that gives results on par with the non-perturbed counterpart. The relative performance of the algorithm is also evaluated on the parallel computing platform Spark. Results show that the technique does not hinder the use of data for holistic analysis while privacy is subjectively maintained.

The Effectiveness of Privacy Policy Statements

2011 ◽  
pp. 84-111
Author(s):  
Roger Clarke
Keyword(s):  
Web Sites ◽  
Personal Data ◽  
Research Literature ◽  
Consumer Trust ◽  
Privacy Policy ◽  
Internet Commerce ◽  
Privacy And Security ◽  
Security Practices ◽  
Policy Statements ◽  
Business To Consumer

An expectation exists in the U.S.A. that operators of business-to-consumer (B2C) Web sites will provide public notice of their privacy and security practices in relation to the personal data that they hold. Such documents are referred to in this paper as Privacy Policy Statements (PPS). The use of PPS has become mainstream in many other countries as well. Privacy and security of personal data are important elements in consumer trust, and hence in a consumer‘s decision to make purchases using Internet commerce services. PPS could therefore be expected to play an important role in overcoming the impediments to consumer purchases online. This paper adds to the growing research literature on PPS by developing a research design involving comparison of an organisation’s PPS against a normative template developed on the basis of professional practice and laws, policies, practices, and public expectations around the world. A study of six B2C sites was undertaken, in order to assess the practicability of the design, and provide some initial substantive insight into the contributions that PPS currently make to consumer trust. It appears that many organisations’ PPS may be seriously inadequate, and hence may be more of an impediment to trust than an enabler of Web-commerce adoption.

scholarly journals Enhanced Framework for Ensuring Privacy Preserving Image Retrieval in Cloud

2019 ◽  
Vol 8 (12) ◽  
pp. 2127-2132
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
Research Work ◽  
Image Data ◽  
Cloud Service ◽  
Sensitive Information ◽  
Cloud Platform ◽  
Privacy And Security ◽  
Computing Platform ◽  
Computing Platforms

Large scale of images data sets are being produced every day by various digital devices. Due to huge computational jobs make people seizure to cloud platforms for their efficient & economical reckoning resources. These computing platforms in which assets are provided as services of the internet. Sensitive information stored in cloud makes more challenging in data security and access control. Once data is uploaded to cloud-platform, the privacy and security of image-data fully depend and believe upon cloud service provider honesty. Our proposed work deals with securing image where high protections are applied on multimedia contents. This paper deals with studies security challenges algorithms lies in image at the time of constructing cloud platform. In this a new enhanced security technique investigated, includes secure by using computation and encryption, act as a security information guard for high secrecy in cloud platform data storage areas. In our research work, cipher-text image is created and performing encryption-decryption at User level. Data hiding and ECC (Elliptic curve cryptosystem) based watermarking technique at cloud computing platform.

Predicting Node Failures in an Ultra-Large-Scale Cloud Computing Platform

2020 ◽  
Vol 29 (2) ◽  
pp. 1-24
Author(s):  
Yangguang Li ◽  
Zhen Ming (Jack) Jiang ◽  
Heng Li ◽  
Ahmed E. Hassan ◽  
Cheng He ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Computing Platform ◽  
Cloud Computing Platform ◽  
Node Failures

scholarly journals Limits of data anonymity: lack of public awareness risks trust in health system activities

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Felix Gille ◽  
Caroline Brall
Keyword(s):  
Large Scale ◽  
Public Awareness ◽  
Personal Data ◽  
Public Trust ◽  
Online News ◽  
Healthcare Management ◽  
Contact Tracing ◽  
Common Denominator ◽  
The Public ◽  
Privacy And Anonymity

AbstractPublic trust is paramount for the well functioning of data driven healthcare activities such as digital health interventions, contact tracing or the build-up of electronic health records. As the use of personal data is the common denominator for these healthcare activities, healthcare actors have an interest to ensure privacy and anonymity of the personal data they depend on. Maintaining privacy and anonymity of personal data contribute to the trustworthiness of these healthcare activities and are associated with the public willingness to trust these activities with their personal data. An analysis of online news readership comments about the failed care.data programme in England revealed that parts of the public have a false understanding of anonymity in the context of privacy protection of personal data as used for healthcare management and medical research. Some of those commenting demanded complete anonymity of their data to be willing to trust the process of data collection and analysis. As this demand is impossible to fulfil and trust is built on a false understanding of anonymity, the inability to meet this demand risks undermining public trust. Since public concerns about anonymity and privacy of personal data appear to be increasing, a large-scale information campaign about the limits and possibilities of anonymity with respect to the various uses of personal health data is urgently needed to help the public to make better informed choices about providing personal data.

Massive Image Treatment System Based on Cloud Computing Platform

2014 ◽  
Vol 687-691 ◽  
pp. 3733-3737
Author(s):  
Dan Wu ◽  
Ming Quan Zhou ◽  
Rong Fang Bie
Keyword(s):  
Image Processing ◽  
Cloud Computing ◽  
High Performance ◽  
Large Scale ◽  
Processing System ◽  
Virtual Space ◽  
Image Processing System ◽  
Computing Platform ◽  
Simulation Calculation ◽  
Computer Resources

Massive image processing technology requires high requirements of processor and memory, and it needs to adopt high performance of processor and the large capacity memory. While the single or single core processing and traditional memory can’t satisfy the need of image processing. This paper introduces the cloud computing function into the massive image processing system. Through the cloud computing function it expands the virtual space of the system, saves computer resources and improves the efficiency of image processing. The system processor uses multi-core DSP parallel processor, and develops visualization parameter setting window and output results using VC software settings. Through simulation calculation we get the image processing speed curve and the system image adaptive curve. It provides the technical reference for the design of large-scale image processing system.

Scalable Data Analytics from Predevelopment to Large Scale Manufacturing

2019 ◽  
Author(s):  
Heiner Heimes ◽  
Achim Kampker ◽  
Ulrich Buhrer ◽  
Anita Steinberger ◽  
Joscha Eirich ◽  
...  
Keyword(s):  
Data Analytics ◽  
Large Scale

scholarly journals Public health platforms: an emerging informatics approach to health professional learning and development

2016 ◽  
Vol 5 (1) ◽  
Author(s):  
Kathleen Gray
Keyword(s):  
Public Health ◽  
Health Professional ◽  
Health Systems ◽  
Professional Learning ◽  
Health Informatics ◽  
Large Scale ◽  
Learning Activities ◽  
Learning And Development ◽  
Use Of Data ◽  
Design Of Learning Environments

Health informatics has a major role to play in optimising the management and use of data, information and knowledge in health systems. As health systems undergo digital transformation, it is important to consider informatics approaches not only to curriculum content but also to the design of learning environments and learning activities for health professional learning and development. An example of such an informatics approach is the use of large-scale, integrated public health platforms on the Internet as part of health professional learning and development. This article describes selected examples of such platforms, with a focus on how they may influence the direction of health professional learning and development.

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