Enabling Trustworthiness in Sustainable Energy Infrastructure Through Blockchain and AI-Assisted Solutions

Document Type

Article

Source of Publication

IEEE wireless communications

Publication Date

12-1-2021

Abstract

Network trustworthiness is a critical component of network security, as it builds on positive inter-actions, guarantees, transparency, and accountability. And with the growth of smart city services and applications, trustworthiness is becoming more important. Most current network trustworthiness solutions are insufficient, particularly for critical infrastructures where end devices are vulnerable and easily hacked. In terms of the energy sector, blockchain technology transforms all currencies into digital modes, thereby allowing one person to manage and exchange energy with others. This has drawn the attention of experts in many fields as a safe, low-cost platform to track billions of transactions in a distributed energy economy. Security and trust issues are still relatively new in the current centralized energy management scheme. With blockchain technology, a decentralized energy infrastructure enables parties to establish micro- grid trading energy transactions and apply artificial intelligence (AI). Using AI in energy systems enables machines to learn various parameters, such as predicted required amounts, excess amounts, and trusted partners. In this article, we envision a cooperative and distributed framework based on cutting-edge computing, communication, and intelligence capabilities such as AI and blockchain in the energy sector to enable secure energy trading, remote monitoring, and trustworthiness. The proposed framework can also enable secure energy trading at the edge devices and among multiple devices. There are also discussions on difficulties, issues, and design principles, as well as spotlights on some of the more popular solutions.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Volume

28

Issue

6

Disciplines

Computer Sciences

Keywords

Training, Smart cities, Transforms, Machine learning, Network security, Blockchains, Artificial intelligence

Indexed in Scopus

no

Open Access

no

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