相关论文: A Core Ontology for Privacy Requirements Engineeri…

Today, many industrial processes are undergoing digital transformation, which often requires the integration of well-understood domain models and state-of-the-art machine learning technology in business processes. However, requirements…

Trust has stood out more than ever in the light of recent innovations. Some examples are advances in artificial intelligence that make machines more and more humanlike, and the introduction of decentralized technologies (e.g. blockchains),…

This article details the creation of a novel domain ontology at the intersection of epidemiology, medicine, statistics, and computer science. Using the terminology defined by current legislation, the article outlines a systematic approach…

As privacy issues have gained social salience, entrepreneurs have begun to offer privacy enhancing technologies (PETs) and the U.S. has begun to enact privacy legislation. But "privacy" is an ambiguous notion. In the liberal tradition, it…

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…

Making sure that users understand privacy policies that impact them is a key challenge for a real GDPR deployment. Research studies are mostly carried in English, but in Europe and elsewhere, users speak a language that is not English.…

The advent of large-scale, complex computing systems has dramatically increased the difficulties of securing accesses to systems' resources. To ensure confidentiality and integrity, the exploitation of access control mechanisms has thus…

Large language models (LLMs), renowned for their impressive capabilities in various tasks, have significantly advanced artificial intelligence. Yet, these advancements have raised growing concerns about privacy and security implications. To…

In the current technology environment, users are often in a vulnerable position when it comes to protecting their privacy. Previous efforts to promote privacy protection have largely focused on top-down approaches such as regulation and…

Quality factors like passive voice or sentence length are commonly used in research and practice to evaluate the quality of natural language requirements since they indicate defects in requirements artifacts that potentially propagate to…

The rapid deployment of large language models (LLMs) in consumer applications has led to frequent exchanges of personal information. To obtain useful responses, users often share more than necessary, increasing privacy risks via…

Ontologies are known for their ability to organize rich metadata, support the identification of novel insights via semantic queries, and promote reuse. In this paper, we consider the problem of automated planning, where the objective is to…

Cloud native information systems engineering enables scalable and resilient service infrastructures for all major online offerings. These are built following agile development practices. At the same time, a growing demand for…

The increasing prevalence of large-scale data collection in modern society represents a potential threat to individual privacy. Addressing this threat, for example through privacy-enhancing technologies (PETs), requires a rigorous…

Building an ontology is not only a time-consuming process, but it is also confusing, especially for beginners and the inexperienced. Although ontology developers can take the help of domain experts in building an ontology, they are not…

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…

A privacy policy is a document that states how a company intends to handle and manage their customers' personal data. One of the problems that arises with these privacy policies is that their content might violate data privacy regulations.…

The Solid specification aims to empower data subjects by giving them direct access control over their data across multiple applications. As governments are manifesting their interest in this framework for citizen empowerment and…

Privacy law and regulation have turned to "consent" as the legitimate basis for collecting and processing individuals' data. As governments have rushed to enshrine consent requirements in their privacy laws, such as the California Consumer…

This article argues that security is not enough to fully capture what is at stake in government exceptional access to encrypted data. A conception of privacy as security has little to say about ``lawful-surveillance protocols'' -- an active…