相关论文: Data Curation from Privacy-Aware Agents

We study the problem faced by a data analyst or platform that wishes to collect private data from privacy-aware agents. To incentivize participation, in exchange for this data, the platform provides a service to the agents in the form of a…

In modern information systems different information features, about the same individual, are often collected and managed by autonomous data collection services that may have different privacy policies. Answering many end-users' legitimate…

Collaborative systems, such as Online Social Networks and the Internet of Things, enable users to share privacy sensitive content. Content in these systems is often co-owned by multiple users with different privacy expectations, leading to…

In recent years, the amount of information collected about human beings has increased dramatically. This development has been partially driven by individuals posting and storing data about themselves and friends using online social networks…

Consider a pair of random variables $(X,Y)$ distributed according to a given joint distribution $p_{XY}$. A curator wishes to maximally disclose information about $Y$, while limiting the information leakage incurred on $X$. Adopting mutual…

A surge in data-driven applications enhances everyday life but also raises serious concerns about private information leakage. Hence many privacy auditing tools are emerging for checking if the data sanitization performed meets the privacy…

This paper initiates the study of the testable implications of choice data in settings where agents have privacy preferences. We adapt the standard conceptualization of consumer choice theory to a situation where the consumer is aware of,…

The rise of mobile apps has brought greater convenience and customization for users. However, many apps use analytics services to collect a wide range of user interaction data purportedly to improve their service, while presenting app users…

Data collecting agents in large networks, such as the electric power system, need to share information (measurements) for estimating the system state in a distributed manner. However, privacy concerns may limit or prevent this exchange…

Data cooperatives with fiduciary obligations to members provide a promising direction for the empowerment of individuals through their own personal data. A data cooperative can manage, curate and protect access to the personal data of…

It is becoming increasingly clear that users should own and control their data. Utility providers are also becoming more interested in guaranteeing data privacy. As such, users and utility providers should collaborate in data privacy, a…

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…

Distributed estimation that recruits potentially large groups of humans to collect data about a phenomenon of interest has emerged as a paradigm applicable to a broad range of detection and estimation tasks. However, it also presents a…

Data analytics (such as association rule mining and decision tree mining) can discover useful statistical knowledge from a big data set. But protecting the privacy of the data provider and the data user in the process of analytics is a…

Software systems are ubiquitous, and their use is ingrained in our everyday lives. They enable us to get in touch with people quickly and easily, support us in gathering information, and help us perform our daily tasks. In return, we…

Recent work has constructed economic mechanisms that are both truthful and differentially private. In these mechanisms, privacy is treated separately from the truthfulness; it is not incorporated in players' utility functions (and doing so…

Data anonymization is an approach to privacy-preserving data release aimed at preventing participants reidentification, and it is an important alternative to differential privacy in applications that cannot tolerate noisy data. Existing…

Data collection purposes and their descriptions are presented on almost all privacy notices under the GDPR, yet there is a lack of research focusing on how effective they are at informing users about data practices. We fill this gap by…

We consider a scenario in which a database stores sensitive data of users and an analyst wants to estimate statistics of the data. The users may suffer a cost when their data are used in which case they should be compensated. The analyst…

Modern supply networks are complex interconnected systems. Multi-agent models are increasingly explored to optimise their performance. Most research assumes agents will have full observability of the system by having a single policy…