相关论文: Optimized, Direct Sale of Privacy in Personal-Data…

The question we raise through this paper is: Is it economically feasible to trade consumer personal information with their formal consent (permission) and in return provide them incentives (monetary or otherwise)?. In view of (a) the…

With the proliferation of the digital data economy, digital data is considered as the crude oil in the twenty-first century, and its value is increasing. Keeping pace with this trend, the model of data market trading between data providers…

A personal data market is a platform including three participants: data owners (individuals), data buyers and market maker. Data owners who provide personal data are compensated according to their privacy loss. Data buyers can submit a…

Every time the customer (individual or company) has to release personal information to its service provider (e.g., an online store or a cloud computing provider), it faces a trade-off between the benefits gained (enhanced or cheaper…

Personal data is becoming one of the most essential resources in today's information-based society. Accordingly, there is a growing interest in data markets, which operate data trading services between data providers and data consumers. One…

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…

As personal data have been the new oil of the digital era, there is a growing trend perceiving personal data as a commodity. Although some people are willing to trade their personal data for money, they might still expect limited privacy…

We study a market for private data in which a data analyst publicly releases a statistic over a database of private information. Individuals that own the data incur a cost for their loss of privacy proportional to the differential privacy…

This paper studies optimal mechanisms for collecting and trading data. Consumers benefit from revealing information about their tastes to a service provider because this improves the service. However, the information is also valuable to a…

We study methods to enhance statistical privacy in blockchain transactions. We analyze economic mechanisms for privacy-aware transaction owners whose utility depends not only on the outcome of the mechanism but also negatively on the…

Due to the recent popularity of online social networks, coupled with people's propensity to disclose personal information in an effort to achieve certain gratifications, the problem of navigating the tradeoff between privacy and utility…

From the early days of the information economy, personal data has been its most valuable asset. Despite data protection laws and an acknowledged right to privacy, trading personal information has become a business equated with "trading…

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…

While users claim to be concerned about privacy, often they do little to protect their privacy in their online actions. One prominent explanation for this "privacy paradox" is that when an individual shares her data, it is not just her…

Online offerings such as web search, news portals, and e-commerce applications face the challenge of providing high-quality service to a large, heterogeneous user base. Recent efforts have highlighted the potential to improve performance by…

Privacy-preserving data release mechanisms aim to simultaneously minimize information-leakage with respect to sensitive data and distortion with respect to useful data. Dependencies between sensitive and useful data results in a…

The design of a statistical signal processing privacy problem is studied where the private data is assumed to be observable. In this work, an agent observes useful data $Y$, which is correlated with private data $X$, and wants to disclose…

We propose a novel problem formulation to address the privacy-utility tradeoff, specifically when dealing with two distinct user groups characterized by unique sets of private and utility attributes. Unlike previous studies that primarily…

Since there is, in principle, no reason why third parties should not pay individuals for the use of their data, we introduce a realistic market that would allow these payments to be made while taking into account the privacy attitude of the…

There is a growing trend regarding perceiving personal data as a commodity. Existing studies have built frameworks and theories about how to determine an arbitrage-free price of a given query according to the privacy loss quantified by…