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Journal ArticleDOI

Security and Privacy in Decentralized Energy Trading Through Multi-Signatures, Blockchain and Anonymous Messaging Streams

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TLDR
This paper has implemented a proof-of-concept for decentralized energy trading system using blockchain technology, multi-signatures, and anonymous encrypted messaging streams, enabling peers to anonymously negotiate energy prices and securely perform trading transactions.
Abstract
Smart grids equipped with bi-directional communication flow are expected to provide more sophisticated consumption monitoring and energy trading. However, the issues related to the security and privacy of consumption and trading data present serious challenges. In this paper we address the problem of providing transaction security in decentralized smart grid energy trading without reliance on trusted third parties. We have implemented a proof-of-concept for decentralized energy trading system using blockchain technology, multi-signatures, and anonymous encrypted messaging streams, enabling peers to anonymously negotiate energy prices and securely perform trading transactions. We conducted case studies to perform security analysis and performance evaluation within the context of the elicited security and privacy requirements.

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Citations
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Journal ArticleDOI

BaDS: Blockchain-Based Architecture for Data Sharing with ABS and CP-ABE in IoT

TL;DR: This work proposes a privacy-preserving and user-controlled data sharing architecture with fine-grained access control, based on the blockchain model and attribute-based cryptosystem and the consensus algorithm is the Byzantine fault tolerance mechanism, rather than Proof of Work.
Journal ArticleDOI

Security and Trust in Blockchains: Architecture, Key Technologies, and Open Issues

TL;DR: The work discusses the basic architecture of blockchains as well as its potential security and trust issues at data, network, consensus, smart contract, and application layers, and some open issues are presented and discussed.
Journal ArticleDOI

GUARDIAN: Blockchain-Based Secure Demand Response Management in Smart Grid System

TL;DR: GUARDIAN, a blockchain-based secure demand response management scheme is presented so as to take energy trading decisions securely for managing the overall load of residential, commercial, and industrial sectors.
Journal ArticleDOI

Consortium Blockchain Based Data Aggregation and Regulation Mechanism for Smart Grid

TL;DR: A smart grid data aggregation and regulation mechanism based on consortium blockchain is proposed, and its signcryption algorithm can be applied to multidimensional data acquisition and multiple receivers in the consortium blockchain to meet security requirements for confidentiality and data integrity.
Journal ArticleDOI

Digital Systems in Smart City and Infrastructure: Digital as a Service

Will Serrano
TL;DR: This paper presents the concept of Digital as a Service (DaaS), where any complete digitalization can be implemented independently of its associated physical infrastructure in a Cloud environment and would enable an interoperable Virtual Digital Infrastructure (VDI).
References
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Proceedings ArticleDOI

Smart Grid Privacy via Anonymization of Smart Metering Data

TL;DR: The method described in this paper provides a 3rd party escrow mechanism for authenticated anonymous meter readings which are difficult to associate with a particular smart meter or customer.
Journal ArticleDOI

Dynamic energy-consumption indicators for domestic appliances: environment, behaviour and design

TL;DR: In this paper, the effectiveness of providing paper-based energy-use/saving information with electronic feedback of energy-consumption via smart meters and displays, or "energyconsumption indicators" (ECI) is reviewed.
Book ChapterDOI

Evaluating User Privacy in Bitcoin

TL;DR: This research examines the use of pseudonymity in the Bitcoin network, and the role that it plays in the development of trust and confidence in the system.
Proceedings ArticleDOI

Private memoirs of a smart meter

TL;DR: It is shown that even without a priori knowledge of household activities or prior training, it is possible to extract complex usage patterns from smart meter data using off-the-shelf statistical methods.
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