scholarly journals How Blockchain and AI Enable Personal Data Privacy and Support Cybersecurity

2021 ◽  
Author(s):  
Stanton Heister ◽  
Kristi Yuthas
Keyword(s):  
Artificial Intelligence ◽  
Data Privacy ◽  
Personal Data ◽  
Analytical Models ◽  
Data Sets ◽  
Privacy And Security ◽  
Security Breaches ◽  
Digital Surveillance ◽  
User Data ◽  
And Control

Recent increases in security breaches and digital surveillance highlight the need for improved privacy and security, particularly over users’ personal data. Advances in cybersecurity and new legislation promise to improve data protection. Blockchain and distributed ledger technologies provide novel opportunities for protecting user data through decentralized identity and other privacy mechanisms. These systems can allow users greater sovereignty through tools that enable them to own and control their own data. Artificial intelligence provides further possibilities for enhancing system and user security, enriching data sets, and supporting improved analytical models.

scholarly journals Solutions to Big Data Privacy and Security Challenges Associated With COVID-19 Surveillance Systems

2021 ◽  
Vol 4 ◽  
Author(s):  
Vibhushinie Bentotahewa ◽  
Chaminda Hewage ◽  
Jason Williams
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
Personal Data ◽  
Surveillance Systems ◽  
Privacy Rights ◽  
Personal Privacy ◽  
Privacy And Security ◽  
Digital Surveillance ◽  
Feasible Solutions ◽  
The Impact

The growing dependency on digital technologies is becoming a way of life, and at the same time, the collection of data using them for surveillance operations has raised concerns. Notably, some countries use digital surveillance technologies for tracking and monitoring individuals and populations to prevent the transmission of the new coronavirus. The technology has the capacity to contribute towards tackling the pandemic effectively, but the success also comes at the expense of privacy rights. The crucial point to make is regardless of who uses and which mechanism, in one way another will infringe personal privacy. Therefore, when considering the use of technologies to combat the pandemic, the focus should also be on the impact of facial recognition cameras, police surveillance drones, and other digital surveillance devices on the privacy rights of those under surveillance. The GDPR was established to ensure that information could be shared without causing any infringement on personal data and businesses; therefore, in generating Big Data, it is important to ensure that the information is securely collected, processed, transmitted, stored, and accessed in accordance with established rules. This paper focuses on Big Data challenges associated with surveillance methods used within the COVID-19 parameters. The aim of this research is to propose practical solutions to Big Data challenges associated with COVID-19 pandemic surveillance approaches. To that end, the researcher will identify the surveillance measures being used by countries in different regions, the sensitivity of generated data, and the issues associated with the collection of large volumes of data and finally propose feasible solutions to protect the privacy rights of the people, during the post-COVID-19 era.

scholarly journals Towards an Architecture to Guarantee Both Data Privacy and Utility in the First Phases of Digital Clinical Trials

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4175 ◽  
Author(s):  
Fabio Angeletti ◽  
Ioannis Chatzigiannakis ◽  
Andrea Vitaletti
Keyword(s):  
Clinical Trial ◽  
Real World ◽  
Social Life ◽  
Data Privacy ◽  
Medical Condition ◽  
Personal Data ◽  
Technical Requirements ◽  
Confidential Data ◽  
User Data ◽  
And Control

In the era of the Internet of Things (IoT), drug developers can potentially access a wealth of real-world, participant-generated data that enable better insights and streamlined clinical trial processes. Protection of confidential data is of primary interest when it comes to health data, as medical condition influences daily, professional, and social life. Current approaches in digital trials entail that private user data are provisioned to the trial investigator that is considered a trusted party. The aim of this paper is to present the technical requirements and the research challenges to secure the flow and control of personal data and to protect the interests of all the involved parties during the first phases of a clinical trial, namely the characterization of the potential patients and their possible recruitment. The proposed architecture will let the individuals keep their data private during these phases while providing a useful sketch of their data to the investigator. Proof-of-concept implementations are evaluated in terms of performances achieved in real-world environments.

Towards Indonesia’s integrated broadcast-broadband implementation policy: A comparative analysis of Singapore, Japan and Malaysia

2021 ◽  
Vol 00 (00) ◽  
pp. 1-19
Author(s):  
Diah Yuniarti ◽  
Sri Ariyanti
Keyword(s):  
Data Privacy ◽  
Comparative Method ◽  
Personal Data ◽  
Personal Data Protection ◽  
User Data ◽  
Implementation Policy ◽  
Digital Terrestrial Television ◽  
The Government ◽  
Broadcast Programme ◽  
Over The Top

This study aims to provide recommendations to the government on regulating licence, content and data privacy and protection for integrated broadcast-broadband (IBB) operations in Indonesia, by referencing Singapore, Japan and Malaysia as case studies, considering the need for umbrella regulations for IBB implementation. Singapore and Japan were chosen as countries that have deployed IBB since they have been using hybrid broadcast broadband television (HbbTV) and Hybridcast standards, respectively. Malaysia was chosen because it is a neighbouring country that has conducted trials of the IBB service, bundled with its digital terrestrial television (DTT) service. The qualitative data are analysed using a comparative method. The results show that Indonesia needs to immediately revise its existing Broadcasting Law to accommodate DTT implementation, which is the basis for IBB and the expansion of the broadcaster’s TV business. Learning from Singapore, Indonesia could include over-the-top (OTT) content in its ‘Broadcast Behaviour Guidelines’ and ‘Broadcast Programme Standards’. Data privacy and protection requirements for each entity involved in the IBB ecosystem are necessary due to the vulnerability of IBB service user data leakage. In light of this, the ratification of the personal data protection law, as a legal umbrella, needs to be accelerated.

Privacy-Sensitive Tracking of Behavior with Public Information Systems

2011 ◽  
pp. 95-109
Author(s):  
Chris C. Demchak ◽  
Kurt D. Fenstermacher
Keyword(s):  
Social Order ◽  
Public Information ◽  
Personal Data ◽  
Public Authority ◽  
Security Threats ◽  
Privacy And Security ◽  
The Social ◽  
Public Information Systems ◽  
And Control ◽  
Identity Knowledge

This chapter explores the roles of names and name equivalents in social tracking and control, reviews the amount of privacy-sensitive databases accumulating today in U.S. legacy federal systems, and proposes an alternative that reduces the likelihood of new security policies violating privacy. We focus on the continuing public-authority reliance on unique identifiers, for example, names or national identity numbers, for services and security instead of dissecting a better indicator of security threats found in behavior data. We conclude with a proposed conceptual change to focusing the social-order mission on the behavior of individuals rather than their identities (behavior-identity knowledge model, BIK). It is particularly urgent to consider a different path now as increased interest in biometrics offers an insidious expansion of unique identifiers of highly personal data. E-government can be wonderful for central government’s effectiveness and efficiency in delivering services while also being a disaster for both privacy and security if not regulated legally, institutionally, and technically (with validation and appeal processes) from the outset.

IoT ecosystem faces fragmented future

2019 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Supply Chain ◽  
Internet Of Things ◽  
Data Privacy ◽  
The Internet ◽  
Privacy And Security ◽  
Content Type ◽  
Iot Devices ◽  
The Internet Of Things

Subject IoT ecosystem. Significance The market for the Internet of Things (IoT) or connected devices is expanding rapidly, with no manufacturer currently forecast to dominate the supply chain. This has fragmented the emerging IoT ecosystem, triggering questions about interoperability and cybersecurity of IoT devices. Impacts Firms in manufacturing, transportation and logistics and utilities are expected to see the highest IoT spending in coming years. The pace of IoT adoption is inextricably linked to that of related technologies such as 5G, artificial intelligence and cloud computing. Data privacy and security will be the greatest constraint to IoT adoption.

scholarly journals Developing an App for Cardiovascular Prevention and Scientific Data Collection

2021 ◽  
Author(s):  
Lara Marie Reimer ◽  
Fabian Starnecker ◽  
Heribert Schunkert ◽  
Stephan Jonas
Keyword(s):  
Data Privacy ◽  
Scientific Information ◽  
Scientific Data ◽  
Mobile App ◽  
Long Term Effects ◽  
Privacy And Security ◽  
User Data ◽  
Cvd Prevention ◽  
Acceptance Rates ◽  
The Individual

Background: Mobile apps may encourage a lifestyle that avoids unhealthy behaviors, such as smoking or poor nutrition, which promotes cardiovascular diseases (CVD). Yet, little data is available on the utilization, perception, and long-term effects of such apps to prevent CVD. Objectives: To develop a mobile app concept to reduce the individual CVD risk and collect information addressing research questions on CVD prevention while preserving data privacy and security. Methods: To validate the concept, a prototype will be built, and usability studies will be performed. Results: We expect to determine whether it is possible to reach a broad user base and to collect scientific information while protecting user data sufficiently. Conclusion: To address CVD prevention, we propose a mobile coaching app. We expect high acceptance rates in validation studies.

scholarly journals Alternative personal data governance models

2019 ◽  
Author(s):  
Bastian Greshake Tzovaras ◽  
Mad Price Ball
Keyword(s):  
Artificial Intelligence ◽  
Data Exchange ◽  
Personal Data ◽  
Training Data ◽  
Data Sets ◽  
Data Governance ◽  
Forthcoming Book ◽  
Governance Strategies ◽  
Governance Models ◽  
Self Driving Cars

The not-so-secret ingredient that underlies all successful Artificial Intelligence / Machine Learning (AI/ML) methods is training data. There would be no facial recognition, no targeted advertisements and no self-driving cars if it was not for large enough data sets with which those algorithms have been trained to perform their tasks. Given how central these data sets are, important ethics questions arise: How is data collection performed? And how do we govern its' use? This chapter – part of a forthcoming book – looks at why new data governance strategies are needed; investigates the relation of different data governance models to historic consent approaches; and compares different implementations of personal data exchange models.

Lawsuits may be key to tighter US data privacy rules

2018 ◽  
Keyword(s):  
United States ◽  
First Amendment ◽  
Data Privacy ◽  
Personal Data ◽  
The United States ◽  
Political Campaigns ◽  
Online Privacy ◽  
Content Type ◽  
Political Consulting ◽  
User Data

Significance The move comes after Facebook suspended a UK political consulting firm, Cambridge Analytica, following allegations on March 18 that it improperly obtained personal data on 50 million Facebook users that was subsequently used in political campaigns. The incident has reignited the debates in the United States and elsewhere on online privacy, targeted messaging and whether tech firms are now too powerful to be left to regulate themselves. Impacts First Amendment considerations will limit any efforts to control online political advertising in the United States. Accusations that Facebook facilitated foreign meddling in elections will dog it more than allegations of improper acquisitions of user data. Internal criticism of Facebook's practices by employees, former employees and investors may be greater agents for change than lawmakers.

scholarly journals Data as asset? The measurement, governance, and valuation of digital personal data by Big Tech

2021 ◽  
Vol 8 (1) ◽  
pp. 205395172110173
Author(s):  
Kean Birch ◽  
DT Cochrane ◽  
Callum Ward
Keyword(s):  
Personal Data ◽  
User Engagement ◽  
Control Rights ◽  
The World ◽  
User Data ◽  
Asset Class ◽  
Revenue Streams ◽  
Per Se ◽  
Political Economic ◽  
And Control

Digital personal data is increasingly framed as the basis of contemporary economies, representing an important new asset class. Control over these data assets seems to explain the emergence and dominance of so-called “Big Tech” firms, consisting of Apple, Microsoft, Amazon, Google/Alphabet, and Facebook. These US-based firms are some of the largest in the world by market capitalization, a position that they retain despite growing policy and public condemnation—or “techlash”—of their market power based on their monopolistic control of personal data. We analyse the transformation of personal data into an asset in order to explore how personal data is accounted for, governed, and valued by Big Tech firms and other political-economic actors (e.g., investors). However, our findings show that Big Tech firms turn “users” and “user engagement” into assets through the performative measurement, governance, and valuation of user metrics (e.g., user numbers, user engagement), rather than extending ownership and control rights over personal data per se. We conceptualize this strategy as a form of “techcraft” to center attention on the means and mechanisms that Big Tech firms deploy to make users and user data measurable and legible as future revenue streams.

Data Privacy vs. Data Security

2021 ◽  
pp. 209-235
Author(s):  
Sue Milton
Keyword(s):  
Cyber Security ◽  
Data Security ◽  
Data Privacy ◽  
Personal Data ◽  
Data Access ◽  
Data Governance ◽  
Privacy And Security ◽  
Data Usage ◽  
High Resource ◽  
Nation States

The proliferation of data exposure via social media implies privacy and security are a lost cause. Regulation counters this through personal data usage compliance. Organizations must also keep non-personal data safe from competitors, criminals, and nation states. The chapter introduces leaders to the two data governance fundamentals: data privacy and data security. The chapter argues that data security cannot be achieved until data privacy issues have been addressed. Simply put, data privacy is fundamental to any data usage policy and data security to the data access policy. The fundamentals are then discussed more broadly, covering data and information management, cyber security, governance, and innovations in IT service provisioning. The chapter clarifies the complementary fundamentals and how they reduce data abuse. The link between privacy and security also demystifies the high resource costs in implementing and maintaining security practices and explains why leaders must provide strong IT leadership to ensure IT investment is defined and implemented wisely.

Sign in / Sign up

Export Citation Format

Share Document