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.read more
Citations
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Proceedings ArticleDOI
Trust Requirements in Blockchain Systems: A Preliminary Study
TL;DR: An urgent need and challenge is identified to revisit requirements engineering models to effectively include trust requirements; and to produce a trust engineering taxonomy, models, and techniques for achieving and fulfilling blockchain system trust requirements and goals.
Journal ArticleDOI
P2PEdge: A Decentralised, Scalable P2P Architecture for Energy Trading in Real-Time
Jan Kalbantner,Konstantinos Markantonakis,Darren Hurley-Smith,Raja Naeem Akram,Benjamin Semal +4 more
TL;DR: The main goal of this paper is to propose a model for a decentralised P2P marketplace for trading energy, which addresses the problem of developing security and privacy-aware environments and a Multi-Agent System (MAS) architecture is presented with a focus on security and sustainability.
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An Architecture for Blockchain based Peer to Peer Energy Trading
TL;DR: The proposed P2P ET architecture consists of three layers: Blockchain layer, Off-Blockchain communication layer and Physical layer, which allows performing secure energy trading without compromising system efficiency.
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Task offloading based on deep learning for blockchain in mobile edge computing
TL;DR: This paper proposes a scalable blockchain and a task offloading technique based on the neural network of the mobile edge computing scenario and shows that the approach is very scalable in the mobile scenario.
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Non-Blocking Two Phase Commit Using Blockchain
TL;DR: It is demonstrated that the 2PC blocking can be eliminated at a moderate financial cost, if the blockchain also meets the synchrony requirements, and despite the blockchain being a reliable state-machine, eliminating2PC blocking may well be impossible.
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
G. Wood,Marcus Newborough +1 more
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.