Related papers: Interactive GDPR-Compliant Privacy Policy Generati…
Android users are increasingly concerned with the privacy of their data and security of their devices. To improve the security awareness of users, recent automatic techniques produce security-centric descriptions by performing program…
News recommendation and personalization is not a solved problem. People are growing concerned of their data being collected in excess in the name of personalization and the usage of it for purposes other than the ones they would think…
Differential Privacy (DP) has emerged as a robust framework for privacy-preserving data releases and has been successfully applied in high-profile cases, such as the 2020 US Census. However, in organizational settings, the use of DP remains…
The growing reliance on data-driven applications in sectors such as healthcare, finance, and law enforcement underscores the need for secure, privacy-preserving, and scalable mechanisms for data generation and sharing. Synthetic data…
Privacy policies have become the most critical approach to safeguarding individuals' privacy and digital security. To enhance their presentation and readability, researchers propose the concept of contextual privacy policies (CPPs), aiming…
Automated analysis of privacy policies has proved a fruitful research direction, with developments such as automated policy summarization, question answering systems, and compliance detection. Prior research has been limited to analysis of…
The rapid development and widespread adoption of Generative Artificial Intelligence-based (GAI) applications have greatly enriched our daily lives, benefiting people by enhancing creativity, personalizing experiences, improving…
The federated analysis of sensitive time series has huge potential in various domains, such as healthcare or manufacturing. Yet, to fully unlock this potential, requirements imposed by various stakeholders must be fulfilled, regarding,…
With the increase in the number of privacy regulations, small development teams are forced to make privacy decisions on their own. In this paper, we conduct a mixed-method survey study, including statistical and qualitative analysis, to…
Context: Digital and physical trails of user activities are collected over the use of software applications and systems. As software becomes ubiquitous, protecting user privacy has become challenging. With the increase of user privacy…
When a database is protected by Differential Privacy (DP), its usability is limited in scope. In this scenario, generating a synthetic version of the data that mimics the properties of the private data allows users to perform any operation…
Privacy and ethics of citizens are at the core of the concerns raised by our increasingly digital society. Profiling users is standard practice for software applications triggering the need for users, also enforced by laws, to properly…
The growing use of Machine Learning and Artificial Intelligence (AI), particularly Large Language Models (LLMs) like OpenAI's GPT series, leads to disruptive changes across organizations. At the same time, there is a growing concern about…
Digital and physical footprints are a trail of user activities collected over the use of software applications and systems. As software becomes ubiquitous, protecting user privacy has become challenging. With the increase of user privacy…
Mobile apps frequently request excessive data access, raising significant privacy concerns. While regulations like GDPR emphasize data minimization, they provide limited guidance on concretely defining and enforcing necessary data access.…
Privacy Preserving Synthetic Data Generation (PP-SDG) has emerged to produce synthetic datasets from personal data while maintaining privacy and utility. Differential privacy (DP) is the property of a PP-SDG mechanism that establishes how…
Recent advances in computing have allowed for the possibility to collect large amounts of data on personal activities and private living spaces. To address the privacy concerns of users in this environment, we propose a novel framework…
This paper introduces the strategic approach to regulating personal data and the normative foundations of the European Union's General Data Protection Regulation ('GDPR'). We explain the genesis of the GDPR, which is best understood as an…
Synthetic data is emerging as a cost-effective solution necessary to meet the increasing data demands of AI development, created either from existing knowledge or derived from real data. The traditional classification of synthetic data…
Conversational assistants process personal data and must comply with data protection regulations that require providers to be transparent with users about how their data is handled. Transparency, in a legal sense, demands preciseness,…