Related papers: Privacy threats in intimate relationships
Over the recent years, the availability of datasets containing personal, but anonymized information has been continuously increasing. Extensive research has revealed that such datasets are vulnerable to privacy breaches: being able to…
People are frequently required to send documents, forms, or other materials containing sensitive data (e.g., personal information, medical records, financial data) to remote parties, sometimes without a formal procedure to do so securely.…
Smart devices are becoming inseparable from daily lives and are improving fast for providing intelligent services and remote monitoring and control. In order to provide personalized and customized services more personal data collection is…
Romantic AI chatbots have quickly attracted users, but their emotional use raises concerns about privacy and safety. As people turn to these systems for intimacy, comfort, and emotionally significant interaction, they often disclose highly…
The increasing popularity of social media has attracted a huge number of people to participate in numerous activities on a daily basis. This results in tremendous amounts of rich user-generated data. This data provides opportunities for…
As privacy issues have gained social salience, entrepreneurs have begun to offer privacy enhancing technologies (PETs) and the U.S. has begun to enact privacy legislation. But "privacy" is an ambiguous notion. In the liberal tradition, it…
The exchange of personal information in digital environments poses significant risks, including identity theft, privacy breaches, and data misuse. Addressing these challenges requires a deep understanding of user behavior and mental models…
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…
Assistive technologies increasingly support independence, accessibility, and safety for older adults, people with disabilities, and individuals requiring continuous care. Two major categories are virtual assistive systems and robotic…
The concept of privacy is inherently intertwined with human attitudes and behaviours, as most computer systems are primarily designed for human use. Especially in the case of Recommender Systems, which feed on information provided by…
Data providers such as government statistical agencies perform a balancing act: maximising information published to inform decision-making and research, while simultaneously protecting privacy. The emergence of identified administrative…
Dating apps for mobile devices, one popular GeoSocial app category, are growing increasingly popular. These apps encourage the sharing of more personal information than conventional social media apps, including continuous location data.…
In distributed learning settings, models are iteratively updated with shared gradients computed from potentially sensitive user data. While previous work has studied various privacy risks of sharing gradients, our paper aims to provide a…
So far, privacy models follow two paradigms. The first paradigm, termed inferential privacy in this paper, focuses on the risk due to statistical inference of sensitive information about a target record from other records in the database.…
Fine-tuning has emerged as a critical process in leveraging Large Language Models (LLMs) for specific downstream tasks, enabling these models to achieve state-of-the-art performance across various domains. However, the fine-tuning process…
Abusers increasingly use spyware apps, account compromise, and social engineering to surveil their intimate partners, causing substantial harms that can culminate in violence. This form of privacy violation, termed intimate partner…
We propose a practical methodology to protect a user's private data, when he wishes to publicly release data that is correlated with his private data, in the hope of getting some utility. Our approach relies on a general statistical…
In the recent time, the problem of protecting privacy in statistical data before they are published has become a pressing one. Many reliable studies have been accomplished, and loads of solutions have been proposed. Though, all these…
The correlations and network structure amongst individuals in datasets today---whether explicitly articulated, or deduced from biological or behavioral connections---pose new issues around privacy guarantees, because of inferences that can…
As more business activities are being automated and an increasing number of computers are being used to store vital and sensitive information the need for secure computer systems becomes more apparent. These systems can be achieved only…