scholarly journals Decentralized Privacy-Preserving Timed Execution in Blockchain-Based Smart Contract Platforms

2018 ◽  
Author(s):  
Chao Li ◽  
Balaji Palanisamy
Keyword(s):  
Privacy Preserving ◽  
Smart Contract

scholarly journals A Transparent and Privacy-preserving Healthcare Platform with Novel Smart Contract for Smart Cities

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Abdullah Al Omar ◽  
Abu Kaisar Jamil ◽  
Amith Khandakar ◽  
Abdur Razzak Uzzal ◽  
Rabeya Bosri ◽  
...  
Keyword(s):  
Smart Cities ◽  
Privacy Preserving ◽  
Smart Contract

scholarly journals SABlockFL: a blockchain-based smart agent system architecture and its application in federated learning

2020 ◽  
Vol 4 (2) ◽  
pp. 133-147
Author(s):  
Zhizhao Zhang ◽  
Tianzhi Yang ◽  
Yuan Liu
Keyword(s):  
Neural Network ◽  
System Architecture ◽  
Data Exchange ◽  
Privacy Preserving ◽  
Agent System ◽  
Content Type ◽  
New Era ◽  
Agent Model ◽  
Blockchain Technology ◽  
Smart Contract

Purpose The purpose of this work is to bridge FL and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. FL is an emerging collaborative machine learning technique that trains a model across multiple devices or servers holding private data samples without exchanging their data. The locally trained results are aggregated by a centralized server in a privacy-preserving way. However, there is an assumption where the centralized server is trustworthy, which is impractical. Fortunately, blockchain technology has opened a new era of data exchange among trustless strangers because of its decentralized architecture and cryptography-supported techniques. Design/methodology/approach In this study, the author proposes a novel design of a smart agent inspired by the smart contract concept. Specifically, based on the proposed smart agent, a fully decentralized, privacy-preserving and fair deep learning blockchain-FL framework is designed, where the agent network is consistent with the blockchain network and each smart agent is a participant in the FL task. During the whole training process, both the data and the model are not at the risk of leakage. Findings A demonstration of the proposed architecture is designed to train a neural network. Finally, the implementation of the proposed architecture is conducted in the Ethereum development, showing the effectiveness and applicability of the design. Originality/value The author aims to investigate the feasibility and practicality of linking the three areas together, namely, multi-agent system, FL and blockchain. A blockchain-FL framework, which is based on a smart agent system, has been proposed. The author has made several contributions to the state-of-the-art. First of all, a concrete design of a smart agent model is proposed, inspired by the smart contract concept in blockchain. The smart agent is autonomous and is able to disseminate, verify the information and execute the supported protocols. Based on the proposed smart agent model, a new architecture composed by these agents is formed, which is a blockchain network. Then, a fully decentralized, privacy-preserving and smart agent blockchain-FL framework has been proposed, where a smart agent acts as both a peer in a blockchain network and a participant in a FL task at the same time. Finally, a demonstration to train an artificial neural network is implemented to prove the effectiveness of the proposed framework.

scholarly journals EtherYou: Ethereum-based privacy-preserving social media platform

2020 ◽  
Author(s):  
Pedro Ivo de Castro Oyama ◽  
Jó Ueyama ◽  
Paulo Matias
Keyword(s):  
Social Media ◽  
Privacy Preserving ◽  
Operating Costs ◽  
Cryptographic Primitives ◽  
Daily Lives ◽  
Maintenance Costs ◽  
Social Media Platform ◽  
Smart Contract ◽  
Media Platform ◽  
Data Transparency

Social media has become part of our daily lives. It brought significant developments in the way we communicate, but it also raised some concerns, including privacy and censorship. In this context, this work presents a social media platform -- EtherYou -- that makes use of cryptographic primitives and an Ethereum smart contract to overcome these issues. Experiments were conducted to evaluate the operating costs involved. The results showed considerable values for senders, zero for receivers, and zero maintenance costs, indicating its potential in scenarios with a reduced number of content producers and a large number of consumers. The proposal offers users privacy over their data, transparency on the system behaviour and censorship resistance.

scholarly journals A Fair and Privacy-Preserving Image Trading System Based on Blockchain and Group Signature

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Le Wang ◽  
Xuefeng Liu ◽  
Xiaodong Lin
Keyword(s):  
Private Information ◽  
Service Providers ◽  
Privacy Preserving ◽  
Group Signature ◽  
Communication Overhead ◽  
Source Image ◽  
User Privacy ◽  
Trading System ◽  
Daily Lives ◽  
Smart Contract

With the rise of digital images in our daily lives, there is a growing need to provide an image trading market where people can monetize their images and get desired images at prices that fit their budget. Those images are usually uploaded and stored onto centralized image trading service providers’ servers and the transactions for image trading are processed by these providers. Unfortunately, transaction unfairness and users’ privacy breaches have become major concerns since the service providers might be untrusted and able to manipulate image trading prices and infer users’ private information. Recently, several approaches have been proposed to address the unfairness issue by using the decentralized ledger technique and smart contract, but users’ privacy protection is not considered. In this paper, we propose a fair and privacy-preserving protocol that supports image fair exchange and protect user privacy. In particular, we exploit blockchain and Merkle tree to construct a fair image trading protocol with low communication overhead based on smart contract, which serves as an external judge that resolves disputes between buyers and sellers in image transactions. Moreover, we extend a popular short group signature scheme to protect users’ identity privacy, prevent linkability of transactions from being inferred, and ensure traceability of malicious users who may sell fake images and/or refuse to pay. Finally, we design and build a practical and open-source image trading system to evaluate the performance of our proposed protocol. Experimental results demonstrate its effectiveness and efficiency in real-world applications.

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