Related papers: PRIPEL: Privacy-Preserving Event Log Publishing In…
This thesis focuses on process mining on event data where such a normative specification is absent and, as a result, the event data is less structured. The thesis puts special emphasis on one application domain that fits this description:…
Privacy-preserving analytics is designed to protect valuable assets. A common service provision involves the input data from the client and the model on the analyst's side. The importance of the privacy preservation is fuelled by legal…
Advances in AI, and especially machine learning, are increasingly drawing research interest and efforts towards predictive process monitoring, the subfield of process mining (PM) that concerns predicting next events, process outcomes and…
Procedural texts often describe processes (e.g., photosynthesis and cooking) that happen over entities (e.g., light, food). In this paper, we introduce an algorithm for procedural reading comprehension by translating the text into a general…
Object-Centric Process Mining (OCPM) enables business process analysis from multiple perspectives. For example, an educational path can be examined from the viewpoints of students, teachers, and groups. This analysis depends on…
Traffic inspection is a fundamental building block of many security solutions today. For example, to prevent the leakage or exfiltration of confidential insider information, as well as to block malicious traffic from entering the network,…
Privacy is dynamic, sensitive, and contextual, much like our emotions. Previous studies have explored the interplay between privacy and context, privacy and emotion, and emotion and context. However, there remains a significant gap in…
As Large Language Models (LLMs) become integral to scientific workflows, concerns over the confidentiality and ethical handling of confidential data have emerged. This paper explores data exposure risks through LLM-powered scientific tools,…
Current models for event causality identification (ECI) mainly adopt a supervised framework, which heavily rely on labeled data for training. Unfortunately, the scale of current annotated datasets is relatively limited, which cannot provide…
For systems whose states implicate sensitive information, their privacy is of great concern. While notions like differential privacy have been successfully introduced to dynamical systems, it is still unclear how a system's privacy can be…
Analytics on video recorded by cameras in public areas have the potential to fuel many exciting applications, but also pose the risk of intruding on individuals' privacy. Unfortunately, existing solutions fail to practically resolve this…
In the contemporary business landscape, collaboration across multiple organizations offers a multitude of opportunities, including reduced operational costs, enhanced performance, and accelerated technological advancement. The application…
Our goal is procedural text comprehension, namely tracking how the properties of entities (e.g., their location) change with time given a procedural text (e.g., a paragraph about photosynthesis, a recipe). This task is challenging as the…
LLM agents have begun to appear as personal assistants, customer service bots, and clinical aides. While these applications deliver substantial operational benefits, they also require continuous access to sensitive data, which increases the…
The mean time between failures (MTBF) of HPC systems is rapidly reducing, and that current failure recovery mechanisms e.g., checkpoint-restart, will no longer be able to recover the systems from failures. Early failure detection is a new…
In-context learning (ICL)-the ability of transformer-based models to perform new tasks from examples provided at inference time-has emerged as a hallmark of modern language models. While recent works have investigated the mechanisms…
Location privacy-preserving mechanisms (LPPMs) have been extensively studied for protecting a user's location at each time point or a sequence of locations with different timestamps (i.e., a trajectory). We argue that existing LPPMs are not…
Releasing Web query logs which contain valuable information for research or marketing, can breach the privacy of search engine users. Therefore rendering query logs to limit linking a query to an individual while preserving the data…
Privacy is a fundamental human right. Data privacy is protected by different regulations, such as GDPR. However, modern large language models require a huge amount of data to learn linguistic variations, and the data often contains private…
System logs constitute valuable information for analysis and diagnosis of system behavior. The size of parallel computing systems and the number of their components steadily increase. The volume of generated logs by the system is in…