Evaluating the Effects of Digital Privacy Regulations on User Trust
- URL: http://arxiv.org/abs/2409.02614v1
- Date: Wed, 4 Sep 2024 11:11:41 GMT
- Title: Evaluating the Effects of Digital Privacy Regulations on User Trust
- Authors: Mehmet Berk Cetin,
- Abstract summary: The study investigates the impact of digital privacy laws on user trust by comparing regulations in the Netherlands, Ghana, and Malaysia.
The main findings reveal that while the General Protection Regulation in the Netherlands is strict, its practical impact is limited by challenges enforcement.
In Ghana, Data Protection Act is underutilized due to low public awareness and insufficient enforcement, leading to reliance on personal protective measures.
In Malaysia, trust in digital services is largely dependent on the security practices of individual platforms rather than the Personal Data Protection Act.
- Score: 0.0
- License: http://creativecommons.org/publicdomain/zero/1.0/
- Abstract: In today's digital society, issues related to digital privacy have become increasingly important. Issues such as data breaches result in misuse of data, financial loss, and cyberbullying, which leads to less user trust in digital services. This research investigates the impact of digital privacy laws on user trust by comparing the regulations in the Netherlands, Ghana, and Malaysia. The study employs a comparative case study method, involving interviews with digital privacy law experts, IT educators, and consumers from each country. The main findings reveal that while the General Data Protection Regulation (GDPR) in the Netherlands is strict, its practical impact is limited by enforcement challenges. In Ghana, the Data Protection Act is underutilized due to low public awareness and insufficient enforcement, leading to reliance on personal protective measures. In Malaysia, trust in digital services is largely dependent on the security practices of individual platforms rather than the Personal Data Protection Act. The study highlights the importance of public awareness, effective enforcement, and cultural considerations in shaping the effectiveness of digital privacy laws. Based on these insights, a recommendation framework is proposed to enhance digital privacy practices, also aiming to provide valuable guidance for policymakers, businesses, and citizens in navigating the challenges of digitalization.
Related papers
- Perception of Digital Privacy Protection: An Empirical Study using GDPR Framework [0.22628031081632272]
This study investigates people perception of digital privacy protection of government data using the General Data Protection Perception Regulation ( systems dichotomy) framework.
Findings suggest a dichotomy in perception in protecting people privacy rights.
The right to object by granting and with-drawing consent is perceived as the least protected.
Second, the study shows evidence of a social dilemma in people perception of digital privacy based on their context and culture.
arXiv Detail & Related papers (2024-11-19T04:36:31Z) - Enabling Humanitarian Applications with Targeted Differential Privacy [0.39462888523270856]
This paper develops an approach to implementing algorithmic decisions based on personal data.
It provides formal privacy guarantees to data subjects.
We show that stronger privacy guarantees typically come at some cost.
arXiv Detail & Related papers (2024-08-24T01:34:37Z) - Collection, usage and privacy of mobility data in the enterprise and public administrations [55.2480439325792]
Security measures such as anonymization are needed to protect individuals' privacy.
Within our study, we conducted expert interviews to gain insights into practices in the field.
We survey privacy-enhancing methods in use, which generally do not comply with state-of-the-art standards of differential privacy.
arXiv Detail & Related papers (2024-07-04T08:29:27Z) - A Critical Take on Privacy in a Datafied Society [0.0]
I analyze several facets of the lack of online privacy and idiosyncrasies exhibited by privacy advocates.
I discuss of possible effects of datafication on human behavior, the prevalent market-oriented assumption at the base of online privacy, and some emerging adaptation strategies.
A glimpse on the likely problematic future is provided with a discussion on privacy related aspects of EU, UK, and China's proposed generative AI policies.
arXiv Detail & Related papers (2023-08-03T11:45:18Z) - Protecting User Privacy in Online Settings via Supervised Learning [69.38374877559423]
We design an intelligent approach to online privacy protection that leverages supervised learning.
By detecting and blocking data collection that might infringe on a user's privacy, we can restore a degree of digital privacy to the user.
arXiv Detail & Related papers (2023-04-06T05:20:16Z) - An Example of Privacy and Data Protection Best Practices for Biometrics
Data Processing in Border Control: Lesson Learned from SMILE [0.9442139459221784]
Misuse of data, compromising the privacy of individuals and/or authorized processing of data may be irreversible.
This is partly due to the lack of methods and guidance for the integration of data protection and privacy by design in the system development process.
We present an example of privacy and data protection best practices to provide more guidance for data controllers and developers.
arXiv Detail & Related papers (2022-01-10T15:34:43Z) - Digital Divide and Social Dilemma of Privacy Preservation [0.6261444979025642]
"Digital privacy divide (DPD)" is introduced to describe the perceived gap in the privacy preservation of individuals based on the geopolitical location of different countries.
We created an online questionnaire and collected answers from more than 700 respondents from four different countries.
Individuals residing in Germany and Bangladesh share similar privacy concerns, while there is a significant similarity among individuals residing in the United States and India.
arXiv Detail & Related papers (2021-10-06T11:43:46Z) - Second layer data governance for permissioned blockchains: the privacy
management challenge [58.720142291102135]
In pandemic situations, such as the COVID-19 and Ebola outbreak, the action related to sharing health data is crucial to avoid the massive infection and decrease the number of deaths.
In this sense, permissioned blockchain technology emerges to empower users to get their rights providing data ownership, transparency, and security through an immutable, unified, and distributed database ruled by smart contracts.
arXiv Detail & Related papers (2020-10-22T13:19:38Z) - PCAL: A Privacy-preserving Intelligent Credit Risk Modeling Framework
Based on Adversarial Learning [111.19576084222345]
This paper proposes a framework of Privacy-preserving Credit risk modeling based on Adversarial Learning (PCAL)
PCAL aims to mask the private information inside the original dataset, while maintaining the important utility information for the target prediction task performance.
Results indicate that PCAL can learn an effective, privacy-free representation from user data, providing a solid foundation towards privacy-preserving machine learning for credit risk analysis.
arXiv Detail & Related papers (2020-10-06T07:04:59Z) - A vision for global privacy bridges: Technical and legal measures for
international data markets [77.34726150561087]
Despite data protection laws and an acknowledged right to privacy, trading personal information has become a business equated with "trading oil"
An open conflict is arising between business demands for data and a desire for privacy.
We propose and test a vision of a personal information market with privacy.
arXiv Detail & Related papers (2020-05-13T13:55:50Z) - Beyond privacy regulations: an ethical approach to data usage in
transportation [64.86110095869176]
We describe how Federated Machine Learning can be applied to the transportation sector.
We see Federated Learning as a method that enables us to process privacy-sensitive data, while respecting customer's privacy.
arXiv Detail & Related papers (2020-04-01T15:10:12Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.