相关论文: Integrating PETs into Software Applications: A Gam…
In the absence of data protection measures, software applications lead to privacy breaches, posing threats to end-users and software organisations. Privacy Enhancing Technologies (PETs) are technical measures that protect personal data,…
Software privacy provides the ability to limit data access to unauthorized parties. Privacy is achieved through different means, such as implementing GDPR into software applications. However, previous research revealed that the lack of poor…
Privacy and data protection constitute core values of individuals and of democratic societies. There have been decades of debate on how those values -and legal obligations- can be embedded into systems, preferably from the very beginning of…
To create privacy-friendly software designs, architects need comprehensive knowledge of existing privacy-enhancing technologies (PETs) and their properties. Existing works that systemize PETs, however, are outdated or focus on comparison…
Privacy-enhancing technologies (PETs) are becoming increasingly crucial for addressing customer needs, security, privacy (e.g., enhancing anonymity and confidentiality), and regulatory requirements. However, applying PETs in organizations…
Artificial intelligence (AI) models introduce privacy vulnerabilities to systems. These vulnerabilities may impact model owners or system users; they exist during model development, deployment, and inference phases, and threats can be…
With smartphone technologies enhanced way of interacting with the world around us, it has also been paving the way for easier access to our private and personal information. This has been amplified by the existence of numerous embedded…
Privacy enhancing technologies, or PETs, have been hailed as a promising means to protect privacy without compromising on the functionality of digital services. At the same time, and partly because they may encode a narrow conceptualization…
Software applications continue to challenge user privacy when users interact with them. Privacy practices (e.g. Data Minimisation (DM), Privacy by Design (PbD) or General Data Protection Regulation (GDPR)) and related "privacy engineering"…
Privacy is an instance of a social norm formed through legal, technical, and cultural dimensions. Institutions such as regulators, industry, and researchers act as societal agents that both influence and respond to evolving norms. Attempts…
As artificial intelligence (AI) continues to permeate various sectors, safeguarding personal and sensitive data has become increasingly crucial. To address these concerns, privacy-enhancing technologies (PETs) have emerged as a suite of…
Privacy-enhancing technologies (PETs) represent a critical operational challenge for the online advertising industry, requiring substantial infrastructure investment while promising improved consumer privacy protection. Even when PETs may…
In a world where data is the new currency, wearable health devices offer unprecedented insights into daily life, continuously monitoring vital signs and metrics. However, this convenience raises privacy concerns, as these devices collect…
Advancements in wearable medical devices in IoT technology are shaping the modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT), we are witnessing how efficient healthcare services are provided to…
As people across the world become increasingly aware of how their privacy is compromised in this digital era, the field of Privacy Enhancing Technologies, or PETs, has boomed. The first workshop on Privacy Enhancing Technology was in 2000,…
We measure how effective Privacy Enhancing Technologies (PETs) are at protecting users from website fingerprinting. Our measurements use both experimental and observational methods. Experimental methods allow control, precision, and use on…
With the extensive use of machine learning technologies, data providers encounter increasing privacy risks. Recent legislation, such as GDPR, obligates organizations to remove requested data and its influence from a trained model. Machine…
In this work, we provide an industry research view for approaching the design, deployment, and operation of trustworthy Artificial Intelligence (AI) inference systems. Such systems provide customers with timely, informed, and customized…
Privacy preservation in Internet of Things (IoT) systems requires the use of privacy-enhancing technologies (PETs) built from innovative technologies such as cryptography and artificial intelligence (AI) to create techniques called privacy…
Using Privacy-Enhancing Technologies (PETs) for machine learning often influences the characteristics of a machine learning approach, e.g., the needed computational power, timing of the answers or how the data can be utilized. When…