Related papers: A Noxious Market for Personal Data
A marketplace is defined where the private data of suppliers (e.g., prosumers) are protected, so that neither their identity nor their level of stock is made known to end customers, while they can sell their products at a reduced price. A…
We initiate the study of markets for private data, though the lens of differential privacy. Although the purchase and sale of private data has already begun on a large scale, a theory of privacy as a commodity is missing. In this paper, we…
EU Directive 95/46/EC and the upcoming EU General Data Protection Regulation grant Europeans the right of access to data pertaining to them. Consumers can approach their service providers to obtain all personal data stored and processed…
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…
The General Data Protection Regulation (GDPR) has become a touchstone model for modern privacy law, in part because it empowers consumers with unprecedented control over the use of their personal information. However, this same power may be…
IoT data markets in public and private institutions have become increasingly relevant in recent years because of their potential to improve data availability and unlock new business models. However, exchanging data in markets bears…
A data marketplace is an online venue that brings data owners, data brokers, and data consumers together and facilitates commoditisation of data amongst them. Data pricing, as a key function of a data marketplace, demands quantifying the…
Researchers find weaknesses in current strategies for protecting privacy in large datasets. Many anonymized datasets are reidentifiable, and norms for offering data subjects notice and consent over emphasize individual responsibility. Based…
The design of data markets has gained importance as firms increasingly use machine learning models fueled by externally acquired training data. A key consideration is the externalities firms face when data, though inherently freely…
Central to privacy concerns is that firms may use consumer data to price discriminate. A common policy response is that consumers should be given control over which firms access their data and how. Since firms learn about a consumer's…
Data protection regulations generally afford individuals certain rights over their personal data, including the rights to access, rectify, and delete the data held on them. Exercising such rights naturally requires those with data…
There are growing concerns and anxiety about privacy among the general public especially after the revelations of former NSA contractor and whistleblowers like Edward Snowden and others. While privacy is the fundamental concept of being…
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…
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…
High-resolution individual geolocation data passively collected from mobile phones is increasingly sold in private markets and shared with researchers. This data poses significant security, privacy, and ethical risks: it's been shown that…
Private data query combines mechanism design with privacy protection to produce aggregated statistics from privately-owned data records. The problem arises in a data marketplace where data owners have personalised privacy requirements and…
In this work, we aim to design a data marketplace; a robust real-time matching mechanism to efficiently buy and sell training data for Machine Learning tasks. While the monetization of data and pre-trained models is an essential focus of…
A public decision-making problem consists of a set of issues, each with multiple possible alternatives, and a set of competing agents, each with a preferred alternative for each issue. We study adaptations of market economies to this…
Data markets are emerging as key mechanisms for trading personal and organizational data. Traditional data pricing studies -- such as query-based or arbitrage-free pricing models -- mainly emphasize price consistency and profit maximization…
This paper proposes a regression market for wind agents to monetize data traded among themselves for wind power forecasting. Existing literature on data markets often treats data disclosure as a binary choice or modulates the data quality…