Reinforcement Learning in Blockchain-Enabled IIoT Networks: A Survey of Recent Advances and Open Challenges

Jameel, Furqan; Javaid, Uzair; Khan, Wali Ullah; Aman, Muhammad Naveed; Pervaiz, Haris; Jäntti, Riku

doi:10.3390/su12125161

Cited by 51 publications

(23 citation statements)

References 72 publications

(80 reference statements)

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“…As a revolutionary invention, Bitcoin certainly caught many investor's attention. One index that can be used to determine the popularity of Bitcoin is the total number of wallets created on the Bitcoin networks 1 . This index is currently at record high (around 65.015 million).…”

Section: The Security and Privacy-preserving Features Of Blockchainmentioning

confidence: 99%

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Blockchain-Empowered Mobile Edge Intelligence, Machine Learning and Secure Data Sharing

Du¹,

Miao²,

Tong³

et al. 2022

Blockchain Potential in AI

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Driven by recent advancements in machine learning, mobile edge computing (MEC) and the Internet of things (IoT), artificial intelligence (AI) has become an emerging technology. Traditional machine learning approaches require the training data to be collected and processed in centralized servers. With the advent of new decentralized machine learning approaches and mobile edge computing, the IoT on-device data training has now become possible. To realize AI at the edge of the network, IoT devices can offload training tasks to MEC servers. However, those distributed frameworks of edge intelligence also introduce some new challenges, such as user privacy and data security. To handle these problems, blockchain has been considered as a promising solution. As a distributed smart ledger, blockchain is renowned for high scalability, privacy-preserving, and decentralization. This technology is also featured with automated script execution and immutable data records in a trusted manner. In recent years, as quantum computers become more and more promising, blockchain is also facing potential threats from quantum algorithms. In this chapter, we provide an overview of the current state-of-the-art in these cutting-edge technologies by summarizing the available literature in the research field of blockchain-based MEC, machine learning, secure data sharing, and basic introduction of post-quantum blockchain. We also discuss the real-world use cases and outline the challenges of blockchain-empowered intelligence.

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Section: The Security and Privacy-preserving Features Of Blockchainmentioning

confidence: 99%

“…Devices in this network can still sense and respond to the environment without users' intervention. Enabling artificial intelligence (AI) in IoT has emerged as a hot research topic [1]. However, machine learning is a kind of computational task which is a heavy workload for the IoT devices (IoTDs).…”

Section: Introductionmentioning

confidence: 99%

Blockchain-Empowered Mobile Edge Intelligence, Machine Learning and Secure Data Sharing

Du¹,

Miao²,

Tong³

et al. 2022

Blockchain Potential in AI

View full text Add to dashboard Cite

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“…ElMamy et al [6] Tariq et al [7] Jameel et al [8] Liu et al [9] Kumari et al [10] Salah et al [11] Tahir et al [12] Nguyen et al [13] Xiong et al [14] Yang et al [15] Sekaran et al [16] Fernandez Carames et al [17] Chamola et al [18] Queiroz et al [19] Mollah et al [20] Our Review ElMamy et al [6] surveyed the usage of DLT to mitigate multiple cyber-threats in Industry 4.0. This survey classified the most important cyber-attacks into four classes, including scanning, local to remote, power of root, and denial of service.…”

Section: Reference Ai Mec Recent Advances Trends Research Gapsmentioning

confidence: 99%

“…For AI enabled by blockchain, there exist several literature reviews. Jameel et al [8] surveyed the application of reinforcement learning in blockchain-enabled industrial IoT networks. They pointed out that machine learning (ML) algorithms, such as Q-learning, can improve the performance of the network, in terms of block time minimization and transaction throughput enhancement.…”

Section: Reference Ai Mec Recent Advances Trends Research Gapsmentioning

confidence: 99%

Blockchain-Enabled Edge Intelligence for IoT: Background, Emerging Trends and Open Issues

Wang

Leung

2021

Future Internet

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Blockchain, a distributed ledger technology (DLT), refers to a list of records with consecutive time stamps. This decentralization technology has become a powerful model to establish trust among trustless entities, in a verifiable manner. Motivated by the recent advancement of multi-access edge computing (MEC) and artificial intelligence (AI), blockchain-enabled edge intelligence has become an emerging technology for the Internet of Things (IoT). We review how blockchain-enabled edge intelligence works in the IoT domain, identify the emerging trends, and suggest open issues for further research. To be specific: (1) we first offer some basic knowledge of DLT, MEC, and AI; (2) a comprehensive review of current peer-reviewed literature is given to identify emerging trends in this research area; and (3) we discuss some open issues and research gaps for future investigations. We expect that blockchain-enabled edge intelligence will become an important enabler of future IoT, providing trust and intelligence to satisfy the sophisticated needs of industries and society.

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“…. $15.00 https://doi.org/10.1145/3397166.3412801 contribute to a rush towards commercialization with minimal consideration for security implications [18]. IoT has thus, unfortunately inherited security vulnerabilities from the firmware, software, and hardware of the previous generation.…”

Section: Introductionmentioning

confidence: 99%

Defining trust in IoT environments via distributed remote attestation using blockchain

Javaid

Aman

Sikdar

2020

Proceedings of the Twenty-First International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Netw

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The constantly growing number of Internet of Things (IoT) devices and their resource-constrained nature makes them particularly vulnerable and increasingly attractive for exploitation by cyber criminals. Current estimates commonly reach the tens of billions for the number of connected 'things'. The heterogeneous capabilities of these devices serve as a motivation for resource sharing among them. However, for effective resource sharing, it is essential that trust be retained in the multitude of pervasive and diverse IoT devices. Remote attestation is a well-known technique used to build such trust. Thus, this paper proposes a blockchain based remote attestation protocol to establish trust between IoT devices. The blockchain offers a secure framework for device registration while the attestation is based on Physical Unclonable Functions (PUF). This combination of technologies results in a tamper resistant scheme with protection against physical and proxy attacks. CCS CONCEPTS • Computer systems organization → Peer-to-peer architectures; Embedded and cyber-physical systems; • Security and privacy → Security protocols; Security in hardware;

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Reinforcement Learning in Blockchain-Enabled IIoT Networks: A Survey of Recent Advances and Open Challenges

Cited by 51 publications

References 72 publications

Blockchain-Empowered Mobile Edge Intelligence, Machine Learning and Secure Data Sharing

Blockchain-Empowered Mobile Edge Intelligence, Machine Learning and Secure Data Sharing

Blockchain-Enabled Edge Intelligence for IoT: Background, Emerging Trends and Open Issues

Defining trust in IoT environments via distributed remote attestation using blockchain

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