English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

A personal data market is a platform including three participants: dataowners (individuals), data buyers and market maker. Data owners who providepersonal data are compensated according to their privacy loss. Data buyers cansubmit a query and pay for the result according to their desired accuracy.Market maker coordinates between data owner and buyer. This framework has beenpreviously studied based on differential privacy. However, the previous studyassumes data owners can accept any level of privacy loss and data buyers canconduct the transaction without regard to the financial budget. In this paper,we propose a practical personal data trading framework that is able to strike abalance between money and privacy. In order to gain insights on userpreferences, we first conducted an online survey on human attitude to- wardprivacy and interest in personal data trading. Second, we identify the 5 keyprinciples of personal data market, which is important for designing areasonable trading frame- work and pricing mechanism. Third, we propose areason- able trading framework for personal data which provides an overview ofhow the data is traded. Fourth, we propose a balanced pricing mechanism whichcomputes the query price for data buyers and compensation for data owners(whose data are utilized) as a function of their privacy loss. The main goal isto ensure a fair trading for both parties. Finally, we will conduct anexperiment to evaluate the output of our proposed pricing mechanism incomparison with other previously proposed mechanism.

How to Balance Privacy and Money through Pricing Mechanism in Personal Data Market