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CrowdLED: Towards Crowd-Empowered and Privacy-Preserving Data Sharing Using Smart Contracts

Authors: Constantinos Pouyioukka; Thanassis Giannetsos; Weizhi Meng 0001;

CrowdLED: Towards Crowd-Empowered and Privacy-Preserving Data Sharing Using Smart Contracts

Abstract

In this research paper, we explore how Blockchain technologies and Smart Contracts can be used to fairly reward users for the data they share with advertising networks without compromising anonymity and user privacy. The novelty of using Blockchains alongside such systems is to understand and investigate how a proper and fair exchange of data can ensure that participating users can be kept secure and eliminate aggressive data collection by ad libraries; libraries that are embedded inside the code of smart-phones and web applications for monetization. There are a lot of privacy issues regarding mobile and online advertising: Advertising networks mostly rely on data collection, similar to a crowd-sensing system, but in most cases, neither consent has been granted by the user for the data collection nor a reward has been given to the user as compensation. Making a comparison between the problems identified in mobile and online advertising and the positives of the approach of using Blockchain, we propose “CrowdLED”, a holistic system to address the security and privacy issues discussed throughout the paper.

Country
Denmark
Related Organizations
Keywords

Smart Contracts, Fairness, Privacy, Online advertising, Security, Crowd-sourcing, Blockchains

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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