相关论文: Changes in Conducting Data Protection Risk Assessm…
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…
This paper introduces the HH4AI Methodology, a structured approach to assessing the impact of AI systems on human rights, focusing on compliance with the EU AI Act and addressing technical, ethical, and regulatory challenges. The paper…
Differential privacy (DP) is a mathematical definition of privacy that can be widely applied when publishing data. DP has been recognized as a potential means of adhering to various privacy-related legal requirements. However, it can be…
Context: Regulations, such as the European Accessibility Act (EAA), impact the engineering of software products and services. Managing that impact while providing meaningful inputs to development teams is one of the emerging requirements…
Organisations can use artificial intelligence to make decisions about people for a variety of reasons, for instance, to select the best candidates from many job applications. However, AI systems can have discriminatory effects when used for…
Modern privacy regulations provide a strict mandate for data processing entities to implement appropriate technical measures to demonstrate compliance. In practice, determining what measures are indeed "appropriate" is not trivial,…
This report provides a detailed comparison between the Safety and Security measures proposed in the EU AI Act's General-Purpose AI (GPAI) Code of Practice (Third Draft) and the current commitments and practices voluntarily adopted by…
With increasingly digitalized workplaces, the potential for sophisticated analyses of employee data rises. This increases the relevance of people analytics (PA), which are tools for the behavioral analysis of employees. Despite this…
Differential privacy (DP) -- a principled approach to producing statistical data products with strong, mathematically provable privacy guarantees for the individuals in the underlying dataset -- has seen substantial adoption in practice…
This PhD thesis discusses how European law could improve privacy protection in the area of behavioural targeting. Behavioural targeting, also referred to as online profiling, involves monitoring people's online behaviour, and using the…
Deep learning models are nowadays broadly deployed to solve an incredibly large variety of tasks. However, little attention has been devoted to connected legal aspects. In 2016, the European Union approved the General Data Protection…
Privacy attacks, particularly membership inference attacks (MIAs), are widely used to assess the privacy of generative models for tabular synthetic data, including those with Differential Privacy (DP) guarantees. These attacks often exploit…
The use of software applications is inevitable as they provide different services to users. The software applications collect, store users' data, and sometimes share with the third party, even without the user consent. One can argue that…
In recent years, our society is being plagued by unprecedented levels of privacy and security breaches. To rein in this trend, the European Union, in 2018, introduced a comprehensive legislation called the General Data Protection Regulation…
Differential Privacy (DP) has emerged as a pivotal approach for safeguarding individual privacy in data analysis, yet its practical adoption is often hindered by challenges in the implementation and communication of DP. This paper presents…
The recently introduced General Data Protection Regulation (GDPR) requires that when obtaining information online that could be used to identify individuals, their consents must be obtained. Among other things, this affects many common…
Cybersecurity risk management consists of several steps including the selection of appropriate controls to minimize risks. This is a difficult task that requires to search through all possible subsets of a set of available controls and…
AI creates and exacerbates privacy risks, yet practitioners lack effective resources to identify and mitigate these risks. We present Privy, a tool that guides practitioners without privacy expertise through structured privacy impact…
Privacy risk assessments aim to analyze and quantify the privacy risks associated with new systems. As such, they are critically important in ensuring that adequate privacy protections are built in. However, current methods to quantify…
In light of the GDPR, data controllers (DC) need to allow data subjects (DS) to exercise certain data subject rights. A key requirement here is that DCs can reliably authenticate a DS. Due to a lack of clear technical specifications, this…