Related papers: Business Process Privacy Analysis in Pleak

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…

Process mining techniques help to improve processes using event data. Such data are widely available in information systems. However, they often contain highly sensitive information. For example, healthcare information systems record event…

Process mining is a new emerging research trend over the last decade which focuses on analyzing the processes using event log and data. The raising integration of information systems for the operation of business processes provides the…

Data science pipelines to train and evaluate models with machine learning may contain bugs just like any other code. Leakage between training and test data can lead to overestimating the model's accuracy during offline evaluations, possibly…

Ever-increasingly complex business processes are enabled by loosely coupled cloud-native systems. In such fast-paced development environments, data controllers face the challenge of capturing and updating all personal data processing…

Data leakage remains a recurrent source of optimistic bias in biomedical machine learning studies. Standard row-wise cross-validation and globally estimated preprocessing steps are often inappropriate for data with repeated measurements,…

The process of linking databases that contain sensitive information about individuals across organisations is an increasingly common requirement in the health and social science research domains, as well as with governments and businesses.…

Privacy and confidentiality are very important prerequisites for applying process mining in order to comply with regulations and keep company secrets. This paper provides a foundation for future research on privacy-preserving and…

Process mining enables business owners to discover and analyze their actual processes using event data that are widely available in information systems. Event data contain detailed information which is incredibly valuable for providing…

We study privacy leakage in the reasoning traces of large reasoning models used as personal agents. Unlike final outputs, reasoning traces are often assumed to be internal and safe. We challenge this assumption by showing that reasoning…

The problem of private information "leakage" (inadvertently or by malicious design) from the myriad large centralized searchable data repositories drives the need for an analytical framework that quantifies unequivocally how safe private…

Process mining methods allow analysts to use logs of historical executions of business processes in order to gain knowledge about the actual behavior of these processes. One of the most widely studied process mining operations is automated…

Protecting sensitive information from unauthorized disclosure is a major concern of every organization. As an organizations employees need to access such information in order to carry out their daily work, data leakage detection is both an…

Quantitative theories of information flow give us an approach to relax the absolute confidentiality properties that are difficult to satisfy for many practical programs. The classical information-theoretic approaches for sequential…

In order to create user-centric and personalized privacy management tools, the underlying models must account for individual users' privacy expectations, preferences, and their ability to control their information sharing activities.…

Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists…

Process mining is a technique that performs an automatic analysis of business processes from a log of events with the promise of understanding how processes are executed in an organisation. Several models have been proposed to address this…

In this report, we present an approach to enhance informed consent for the processing of personal data. The approach relies on a privacy policy language used to express, compare and analyze privacy policies. We describe a tool that…

The application and development of process mining techniques face significant challenges due to the lack of publicly available real-life event logs. One reason for companies to abstain from sharing their data are privacy and confidentiality…

This article explores the gaps that can manifest when using a large language model (LLM) to obtain simplified interpretations of data practices from a complex privacy policy. We exemplify these gaps to showcase issues in accuracy,…