相关论文: A Core Ontology for Privacy Requirements Engineeri…
Authentication systems are designed to give the right person access to an organization's information system and to restrict it from the wrong person. Such systems are designed by IT professionals to protect an organization's assets (e.g.,…
Requirements Engineering has recently been greatly influenced by the way how firms use Open Source Software (OSS) and Software Ecosystems (SECOs) as a part of their product development and business models. This is further emphasized by the…
Research shows that analysts and developers consider privacy as a security concept or as an afterthought, which may lead to non-compliance and violation of users' privacy. Most current approaches, however, focus on extracting legal…
Engineering projects for railway infrastructure typically involve many subsystems which need consistent views of the planned and built infrastructure and its underlying topology. Consistency is typically ensured by exchanging and verifying…
This paper presents a software component that generates a user interface structure for populating a domain ontology. The core of this work is an algorithm that takes an ontology and returns a structure describing the user interface. The…
Many anonymous communication networks (ACNs) with different privacy goals have been developed. However, there are no accepted formal definitions of privacy and ACNs often define their goals and adversary models ad hoc. However, for the…
Rapid advances in human genomics are enabling researchers to gain a better understanding of the role of the genome in our health and well-being, stimulating hope for more effective and cost efficient healthcare. However, this also prompts a…
One of the great challenges the information society faces is dealing with the huge amount of information generated and handled daily on the Internet. Today, progress in Big data proposals attempts to solve this problem, but there are…
In this paper we describe the requirements for research information systems and problems which arise in the development of such system. Here is shown which problems could be solved by using of knowledge markup technologies. Ontology for…
Machine learning community is discovering Contextual Integrity (CI) as a useful framework to assess the privacy implications of large language models (LLMs). This is an encouraging development. The CI theory emphasizes sharing information…
The emergence of large language models (LLMs), and their increased use in user-facing systems, has led to substantial privacy concerns. To date, research on these privacy concerns has been model-centered: exploring how LLMs lead to privacy…
Context-aware reasoning systems allow drawing sophisticated inferences about users' behaviour and physiological condition, by aggregating data from seemingly unrelated sources. We conducted a general population online survey to evaluate…
As language models are increasingly deployed as autonomous agents in high-stakes settings, ensuring that they reliably follow user-defined rules has become a critical safety concern. To this end, we study whether language models exhibit…
Large Language Models (LLMs) have achieved remarkable progress in natural language understanding, reasoning, and autonomous decision-making. However, these advancements have also come with significant privacy concerns. While significant…
Purpose is crucial for privacy protection as it makes users confident that their personal data are processed as intended. Available proposals for the specification and enforcement of purpose-aware policies are unsatisfactory for their…
In the digital age, it is crucial to understand and tailor experiences for users interacting with systems and applications. This requires the creation of user contextual profiles that combine user profiles with contextual information.…
Obfuscation in privacy engineering denotes a diverse set of data operations aimed at reducing the privacy loss that users incur in by participating in digital systems. Obfuscation's domain of application is vast: privacy-preserving database…
Process performance indicators (PPIs) are metrics to quantify the degree with which organizational goals defined based on business processes are fulfilled. They exploit the event logs recorded by information systems during the execution of…
Distributed ledger technology offers numerous desirable attributes to applications in the enterprise context. However, with distributed data and decentralized computation on a shared platform, privacy and confidentiality challenges arise.…
The rapid advancement of large language models (LLMs) has revolutionized natural language processing, enabling applications in diverse domains such as healthcare, finance and education. However, the growing reliance on extensive data for…