Related papers: Faults and Pitfalls in Implementing the Right to b…
Code-related benchmarks play a critical role in evaluating large language models (LLMs), yet their quality fundamentally shapes how the community interprets model capabilities. In the past few years, awareness of benchmark quality has…
The European General Data Protection Regulation (GDPR) grants European users the right to access their data processed and stored by organizations. Although the GDPR contains requirements for data processing organizations (e.g.,…
The growing use of large language models in sensitive domains has exposed a critical weakness: the inability to ensure that private information can be permanently forgotten. Yet these systems still lack reliable mechanisms to guarantee that…
Federated Learning (FL) enables collaborative model training across distributed clients while preserving user privacy. Recently, Federated Unlearning (FU) has emerged to address the "right to be forgotten" and to remove the influence of…
Federated Learning (FL) shows promise in preserving privacy and enabling collaborative learning. However, most current solutions focus on private data collected from a single domain. A significant challenge arises when client data comes…
Training machine learning models requires the storage of large datasets, which often contain sensitive or private data. Storing data is associated with a number of potential risks which increase over time, such as database breaches and…
General Data Protection Regulations (GDPR) aim to safeguard individuals' personal information from harm. While full compliance is mandatory in the European Union and the California Privacy Rights Act (CPRA), it is not in other places. GDPR…
The Internet and cyberspace are inseparable aspects of everyone's life. Cyberspace is a concept that describes widespread, interconnected, and online digital technology. Cyberspace refers to the online world that is separate from everyday…
Conformance checking (CC) techniques of the process mining field gauge the conformance of the sequence of events in a case with respect to a business process model, which simply put is an amalgam of certain behavioral relations or rules.…
Foundation models are commonly deployed as frozen feature extractors with a small trainable head to adapt to private, user-generated data in federated settings. The ``right to be forgotten'' requires removing the influence of specific…
The deployment of large language models (LLMs) like ChatGPT and Gemini has shown their powerful natural language generation capabilities. However, these models can inadvertently learn and retain sensitive information and harmful content…
Individuals are gaining more control of their personal data through recent data privacy laws such the General Data Protection Regulation and the California Consumer Privacy Act. One aspect of these laws is the ability to request a business…
Database research can help machine learning performance in many ways. One way is to design better data structures. This paper combines the use of incremental computation and sequential and probabilistic filtering to enable "forgetful"…
The objective of digital forgetting is, given a model with undesirable knowledge or behavior, obtain a new model where the detected issues are no longer present. The motivations for forgetting include privacy protection, copyright…
Modern data stores increasingly rely on metadata for enabling diverse activities such as data cataloging and search. However, metadata curation remains a labor-intensive task, and the broader challenge of metadata maintenance -- ensuring…
The General Data Protection Regulation (GDPR) in the European Union is the most famous recently enacted privacy regulation. Despite of the regulation's legal, political, and technological ramifications, relatively little research has been…
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…
Software practitioners can make sub-optimal decisions concerning requirements during gathering, documenting, prioritizing, and implementing requirements as software features or architectural design decisions -- this is captured by the…
As concerns about unfairness and discrimination in "black box" machine learning systems rise, a legal "right to an explanation" has emerged as a compellingly attractive approach for challenge and redress. We outline recent debates on the…
Catastrophic forgetting is not an engineering failure. It is a mathematical consequence of storing knowledge as global parameter superposition. Existing methods, such as regularization, replay, and frozen subnetworks, add external…