相关论文: Beware of the Ostrich Policy: End-Users' Perceptio…
We use decision theory to compare variants of differential privacy from the perspective of prospective study participants. We posit the existence of a preference ordering on the set of potential consequences that study participants can…
In opinion polls, the public frequently claim to value their privacy. However, individuals often seem to overlook the principle, contributing to a disparity labelled the `Privacy Paradox'. The growth of the Internet-of-Things (IoT) is…
Modern recommender systems are trained to predict users potential future interactions from users historical behavior data. During the interaction process, despite the data coming from the user side recommender systems also generate exposure…
Access to smart meter data offers system-wide benefits but raises significant privacy concerns due to the personal information it contains. Privacy-preserving techniques could facilitate wider access, though they introduce privacy-utility…
Personal data custodian services enable data owners to share their data with data consumers in a convenient manner, anytime and anywhere. However, with data hosted in these services being beyond the control of the data owners, it raises…
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…
Tabular data sharing serves as a common method for data exchange. However, sharing sensitive information without adequate privacy protection can compromise individual privacy. Thus, ensuring privacy-preserving data sharing is crucial.…
With the growing advances in the Internet of Things (IoT) technology, IoT device management platforms are becoming increasingly important. We conducted a web-based survey and usability study with 43 participants who use IoT devices…
Artificial Intelligence (AI) systems are frequently employed in online services to provide personalized experiences to users based on large collections of data. However, AI systems can be designed in different ways, with black-box AI…
Most companies' new business practices are based on customer data. These practices have raised privacy concerns because of the associated risks. Privacy laws require companies to gain customer consent before using their information, which…
IoT is an emerging area in which we expect to have billions of devices connected to the Internet by 2020. IoT applications can offer many benefits to environments, society and the economy through the interconnection and cooperation of smart…
Profiling users for the purpose of targeted advertisements or other kinds of personalization is very popular on the internet. But besides the benefits of individually tailored news feeds and shopping recommendation research has shown that…
Fairness monitoring is critical for detecting algorithmic bias, as mandated by the EU AI Act. Since such monitoring requires sensitive user data (e.g., ethnicity), the AI Act permits its processing only with strict privacy measures, such as…
Many software systems, such as online social networks enable users to share information about themselves. While the action of sharing is simple, it requires an elaborate thought process on privacy: what to share, with whom to share, and for…
Recommendation systems are widely used in web services, such as social networks and e-commerce platforms, to serve personalized content to the users and, thus, enhance their experience. While personalization assists users in navigating…
Managing privacy to reach privacy goals is challenging, as evidenced by the privacy attitude-behavior gap. Mitigating this discrepancy requires solutions that account for both system opaqueness and users' hesitations in testing different…
The Internet of Behaviors (IoB) is an emerging concept that utilizes devices to collect human behavior and provide intelligent services. Although some research has focused on human behavior analysis and data collection within IoB, the…
Data markets serve as crucial platforms facilitating data discovery, exchange, sharing, and integration among data users and providers. However, the paramount concern of privacy has predominantly centered on protecting privacy of data…
In this paper we present the Privacy Dashboard -- a tool designed to inform and empower the people using mobile devices, by introducing features such as Remote Privacy Protection, Backup, Adjustable Location Accuracy, Permission Control and…
Social networks have become an essential meeting point for millions of individuals willing to publish and consume huge quantities of heterogeneous information. Some studies have shown that the data published in these platforms may contain…