scholarly journals DATA PRIVACY ISSUES IN THE AGE OF DATA BROKERAGE: AN EXPLORATORY LITERATURE REVIEW

2018 ◽  
Keyword(s):  
Literature Review ◽  
Data Privacy ◽  
Privacy Issues

scholarly journals Data privacy during pandemics: a systematic literature review of COVID-19 smartphone applications

2022 ◽  
Vol 7 ◽  
pp. e826
Author(s):  
Amany Alshawi ◽  
Muna Al-Razgan ◽  
Fatima H. AlKallas ◽  
Raghad Abdullah Bin Suhaim ◽  
Reem Al-Tamimi ◽  
...  
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Digital Libraries ◽  
Data Privacy ◽  
Public Law ◽  
Contact Tracing ◽  
Assessment Procedure ◽  
Control And Prevention ◽  
Novel Coronavirus ◽  
Privacy Issues

Background On January 8, 2020, the Centers for Disease Control and Prevention officially announced a new virus in Wuhan, China. The first novel coronavirus (COVID-19) case was discovered on December 1, 2019, implying that the disease was spreading quietly and quickly in the community before reaching the rest of the world. To deal with the virus’ wide spread, countries have deployed contact tracing mobile applications to control viral transmission. Such applications collect users’ information and inform them if they were in contact with an individual diagnosed with COVID-19. However, these applications might have affected human rights by breaching users’ privacy. Methodology This systematic literature review followed a comprehensive methodology to highlight current research discussing such privacy issues. First, it used a search strategy to obtain 808 relevant papers published in 2020 from well-established digital libraries. Second, inclusion/exclusion criteria and the snowballing technique were applied to produce more comprehensive results. Finally, by the application of a quality assessment procedure, 40 studies were chosen. Results This review highlights privacy issues, discusses centralized and decentralized models and the different technologies affecting users’ privacy, and identifies solutions to improve data privacy from three perspectives: public, law, and health considerations. Conclusions Governments need to address the privacy issues related to contact tracing apps. This can be done through enforcing special policies to guarantee users privacy. Additionally, it is important to be transparent and let users know what data is being collected and how it is being used.

scholarly journals Federated Learning in a Medical Context: A Systematic Literature Review

2021 ◽  
Vol 21 (2) ◽  
pp. 1-31
Author(s):  
Bjarne Pfitzner ◽  
Nico Steckhan ◽  
Bert Arnrich
Keyword(s):  
Machine Learning ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Data Privacy ◽  
Research Area ◽  
Learning Models ◽  
Related Data ◽  
Private Data ◽  
Large Databases ◽  
Machine Learning Models

Data privacy is a very important issue. Especially in fields like medicine, it is paramount to abide by the existing privacy regulations to preserve patients’ anonymity. However, data is required for research and training machine learning models that could help gain insight into complex correlations or personalised treatments that may otherwise stay undiscovered. Those models generally scale with the amount of data available, but the current situation often prohibits building large databases across sites. So it would be beneficial to be able to combine similar or related data from different sites all over the world while still preserving data privacy. Federated learning has been proposed as a solution for this, because it relies on the sharing of machine learning models, instead of the raw data itself. That means private data never leaves the site or device it was collected on. Federated learning is an emerging research area, and many domains have been identified for the application of those methods. This systematic literature review provides an extensive look at the concept of and research into federated learning and its applicability for confidential healthcare datasets.

scholarly journals The Challenges of Institutional Distance: Data Privacy Issues in Cloud Computing

2018 ◽  
Vol 24 (1) ◽  
pp. 161-181 ◽  
Author(s):  
Yashar Abed ◽  
Meena Chavan
Keyword(s):  
Cloud Computing ◽  
Multinational Corporations ◽  
Data Privacy ◽  
Service Providers ◽  
Host Countries ◽  
Case Study Methodology ◽  
Regulatory Constraints ◽  
Cloud Computing Service ◽  
Privacy Issues

Data protection and data privacy are significant challenges in cloud computing for multinational corporations. There are no standard laws to protect data across borders. The institutional and regulatory constraints and governance differ across countries. This article explores the challenges of institutional constraints faced by cloud computing service providers in regard to data privacy issues across borders. Through a qualitative case study methodology, this research compares the institutional structure of a few host countries, with regard to data privacy in cloud computing and delineates a relative case study. This article will also review the cloud computing legal frameworks and the history of cloud computing to make the concept more comprehensible to a layman.

Opportunities and Challenges of Big Data in Healthcare

2020 ◽  
pp. 1989-2001
Author(s):  
Wafaa Faisal Mukhtar ◽  
Eltayeb Salih Abuelyaman
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
Ethical Issues ◽  
Standard Of Care ◽  
Healthcare Sector ◽  
Useful Knowledge ◽  
Healthcare Data ◽  
Big Data Streams ◽  
Privacy Issues ◽  
Collection Methods

Healthcare big data streams from multiple information sources at an alarming volume, velocity, and variety. The challenge that faces the healthcare industry is extracting meaningful value from such sources. This chapter investigates the diversity and forms of data in the healthcare sector, reviews the methods used to search and analyze these data throughout the past years, and the use of machine learning and data mining techniques to mine useful knowledge from such data. The chapter will also highlight innovations of particular systems and tools which spot the fine approaches for different healthcare data, raise the standard of care and recap the tools and data collection methods. The authors emphasize some of ethical issues regarding processing these records and some data privacy issues.

scholarly journals A systematic literature review of Native American and Pacific Islanders’ perspectives on health data privacy in the United States

2020 ◽  
Vol 27 (12) ◽  
pp. 1987-1998
Author(s):  
Riley Taitingfong ◽  
Cinnamon S Bloss ◽  
Cynthia Triplett ◽  
Julie Cakici ◽  
Nanibaa’ Garrison ◽  
...  
Keyword(s):  
Native American ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Alaska Native ◽  
Health Research ◽  
Data Privacy ◽  
Indigenous Communities ◽  
The United States ◽  
Health Data ◽  
Willingness To Participate

Abstract Background Privacy-related concerns can prevent equitable participation in health research by US Indigenous communities. However, studies focused on these communities' views regarding health data privacy, including systematic reviews, are lacking. Methods We conducted a systematic literature review analyzing empirical, US-based studies involving American Indian/Alaska Native (AI/AN) and Native Hawaiian or other Pacific Islander (NHPI) perspectives on health data privacy, which we define as the practice of maintaining the security and confidentiality of an individual’s personal health records and/or biological samples (including data derived from biological specimens, such as personal genetic information), as well as the secure and approved use of those data. Results Twenty-one studies involving 3234 AI/AN and NHPI participants were eligible for review. The results of this review suggest that concerns about the privacy of health data are both prevalent and complex in AI/AN and NHPI communities. Many respondents raised concerns about the potential for misuse of their health data, including discrimination or stigma, confidentiality breaches, and undesirable or unknown uses of biological specimens. Conclusions Participants cited a variety of individual and community-level concerns about the privacy of their health data, and indicated that these deter their willingness to participate in health research. Future investigations should explore in more depth which health data privacy concerns are most salient to specific AI/AN and NHPI communities, and identify the practices that will make the collection and use of health data more trustworthy and transparent for participants.

scholarly journals The Machine Age of Marketing: How Artificial Intelligence Changes the Way People Think, Act, and Decide

2019 ◽  
Vol 11 (2) ◽  
pp. 10-17 ◽  
Author(s):  
Christian Hildebrand
Keyword(s):  
Data Privacy ◽  
New Economy ◽  
Business Practice ◽  
Value Chains ◽  
Machine Age ◽  
Private Lives ◽  
Processing Power ◽  
Autonomous Cars ◽  
The World ◽  
Privacy Issues

AbstractWhatever your perception of AI is, the machine age of marketing has arrived. To fully grasp how AI is changing every fabric of both our professional and private lives, we need to abstract beyond the presence of autonomous cars, digital voice assistants, or using machines to translate some text for us. AI is creating new forms of competition, value chains, and novel ways of orchestrating economies around the world. AI is more than just technology, it’s creating a new economy. The fuel that runs this economy is the combination of computational processing power, data, and the algorithms that process this data.AI has the potential to make our life easier, but this convenience might come at a price which we have to pay such as biases directly built-in to the algorithms we use, data privacy issues or failed AI projects in business practice. But without testing, failing, and learning from our failures, there

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