相关论文: Privacy Architectures: Reasoning About Data Minimi…
As Artificial Intelligence (AI) becomes more prevalent, protecting personal privacy is a critical ethical issue that must be addressed. This article explores the need for ethical AI systems that safeguard individual privacy while complying…
The Internet of Things paradigm envisions the pervasive interconnection and cooperation of smart things over the current and future Internet infrastructure. The Internet of Things is, thus, the evolution of the Internet to cover the…
With the arrival of modern internet era, large public networks of various types have come to existence to benefit the society as a whole and several research areas such as sociology, economics and geography in particular. However, the…
The massive growth of the Internet of Things (IoT) as a network of interconnected entities [18], brings up new challenges in terms of privacy and security requirements to the traditional software engineering domain [4]. To protect the…
In the current paradigm of digital personalized services, the centralized management of personal data raises significant privacy concerns, security vulnerabilities, and diminished individual autonomy over sensitive information. Despite…
The rapid growth in digital data forms the basis for a wide range of new services and research, e.g, large-scale medical studies. At the same time, increasingly restrictive privacy concerns and laws are leading to significant overhead in…
As we transition into the era of B5G/6G networks, the promise of seamless, high-speed connectivity brings unprecedented opportunities and challenges. Among the most critical concerns is the preservation of location privacy, given the…
Data privacy legislation, such as GDPR and CCPA/CPRA, has rendered data privacy law compliance a requirement of all software systems. Developers need to implement various kinds of functionalities to cover law needs, including user rights…
In smart grid, large quantities of data is collected from various applications, such as smart metering substation state monitoring, electric energy data acquisition, and smart home. Big data acquired in smart grid applications usually is…
With the arrival of the European Union's General Data Protection Regulation (GDPR), several companies are making significant changes to their systems to achieve compliance. The changes range from modifying privacy policies to redesigning…
Mining health data can lead to faster medical decisions, improvement in the quality of treatment, disease prevention, reduced cost, and it drives innovative solutions within the healthcare sector. However, health data is highly sensitive…
In smart grids, the use of smart meters to measure electricity consumption at a household level raises privacy concerns. To address them, researchers have designed various load hiding algorithms that manipulate the electricity consumption…
Recommender systems are essential for personalizing digital experiences on e-commerce sites, streaming services, and social media platforms. While these systems are necessary for modern digital interactions, they face fairness, bias,…
Users are often overwhelmed by privacy decisions to manage their personal data, which can happen on the web, in mobile, and in IoT environments. These decisions can take various forms -- such as decisions for setting privacy permissions or…
In this literature review, we first briefly provide an introduction on the privacy aspect of blockchain systems and why it is a difficult quality to achieve, especially using traditional methods. Next, we go over a wide range of different…
Today, the publication of microdata poses a privacy threat. Vast research has striven to define the privacy condition that microdata should satisfy before it is released, and devise algorithms to anonymize the data so as to achieve this…
Since the introduction of the European General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), software developers increasingly have to make privacy-related decisions during system design and…
Statistical agencies face a dual mandate to publish accurate statistics while protecting respondent privacy. Increasing privacy protection requires decreased accuracy. Recognizing this as a resource allocation problem, we propose an…
Centralized systems in the Internet of Things---be it local middleware or cloud-based services---fail to fundamentally address privacy of the collected data. We propose an architecture featuring secure multiparty computation at its core in…
Most prominent research today addresses compliance with data protection laws through consumer-centric and public-regulatory approaches. We shift this perspective with the Privatech project to focus on corporations and law firms as agents of…