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Language Models (LMs) have been shown to leak information about training data through sentence-level membership inference and reconstruction attacks. Understanding the risk of LMs leaking Personally Identifiable Information (PII) has…
Many datasets contain personally identifiable information, or PII, which poses privacy risks to individuals. PII masking is commonly used to redact personal information such as names, addresses, and phone numbers from text data. Most modern…
The (generative) artificial intelligence (AI) era has profoundly reshaped the meaning and value of data. No longer confined to static content, data now permeates every stage of the AI lifecycle from the training samples that shape model…
The eruption of big data with the increasing collection and processing of vast volumes and variety of data have led to breakthrough discoveries and innovation in science, engineering, medicine, commerce, criminal justice, and national…
In the current data driven era, synthetic data, artificially generated data that resembles the characteristics of real world data without containing actual personal information, is gaining prominence. This is due to its potential to…
Since its introduction in 2006, differential privacy has emerged as a predominant statistical tool for quantifying data privacy in academic works. Yet despite the plethora of research and open-source utilities that have accompanied its…
Privacy personas capture the differences in user segments with respect to one's knowledge, behavioural patterns, level of self-efficacy, and perception of the importance of privacy protection. Modelling these differences is essential for…
Many smartphone apps transmit personally identifiable information (PII), often without the users knowledge. To address this issue, we present PrivacyProxy, a system that monitors outbound network traffic and generates app-specific…
The proliferation of AI agents, with their complex and context-dependent actions, renders conventional privacy paradigms obsolete. This position paper argues that the current model of privacy management, rooted in a user's unilateral…
Context: Digital and physical trails of user activities are collected over the use of software applications and systems. As software becomes ubiquitous, protecting user privacy has become challenging. With the increase of user privacy…
The increasing availability of personal data has enabled significant advances in fields such as machine learning, healthcare, and cybersecurity. However, this data abundance also raises serious privacy concerns, especially in light of…
The internet is a common place for businesses to collect and store as much client data as possible and computer storage capacity has increased exponentially due to this trend. Businesses utilize this data to enhance customer satisfaction,…
Sanitizing sensitive text data typically involves removing personally identifiable information (PII) or generating synthetic data under the assumption that these methods adequately protect privacy; however, their effectiveness is often only…
In the modern digital world users need to make privacy and security choices that have far-reaching consequences. Researchers are increasingly studying people's decisions when facing with privacy and security trade-offs, the pressing and…
Organisations disclose their privacy practices by posting privacy policies on their website. Even though users often care about their digital privacy, they often don't read privacy policies since they require a significant investment in…
Privacy preferences are not fixed individual traits, they depend on context and lived experiences. In this study, we analyze 2,912 survey responses from 782 college students collected over seven survey periods during 2023 and 2024. We ask…
Privacy policies are the primary channel through which companies inform users about their data collection and sharing practices. These policies are often long and difficult to comprehend. Short notices based on information extracted from…
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…
In the era of big data, there is an increasing need for healthcare providers, communities, and researchers to share data and collaborate to improve health outcomes, generate valuable insights, and advance research. The Health Insurance…
Detecting personally identifiable information (PII) in user queries is critical for ensuring privacy in question-answering systems. Current approaches mainly redact all PII, disregarding the fact that some of them may be contextually…