A Novel & Innovative Blockchain-Empowered Federated Learning Approach for Secure Data Sharing in Smart City Applications

Tao Hai; Dan Wang; Tamizharasi Seetharaman; M. Amelesh; P. M. Sreejith; Vandana Sharma; Ebuka Ibeke; Hong Liu

doi:10.1007/978-3-031-37164-6_9

A Novel & Innovative Blockchain-Empowered Federated Learning Approach for Secure Data Sharing in Smart City Applications

Tao Hai
, Dan Wang
, Tamizharasi Seetharaman
, M. Amelesh
, P. M. Sreejith
, Vandana Sharma
, Ebuka Ibeke
, Hong Liu

Qiannan Normal College for Nationalities
Guizhou University
Nanchang Institute of Science and Technology
Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province
Acharya Institute of Technology
Amity University, Noida
Robert Gordon University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

16 Scopus citations

Abstract

The very existence of smart cities forms the stepping stone in the evolution of many technological advancements in the future era. While smart cities have already grown in their way, the tremendous amount of data generated from them paves the way for new perspectives of development. This is because security and privacy remain to be the major constraint across smart city applications. Further, smart city applications such as smart homes, smart transportation, and smart healthcare are generating a huge amount of data every day and it is often complex to collect and manage all the data together at a single location. To address these constraints, this paper presents a novel and innovative blockchain-assisted federated learning approach for secure data sharing in IoT Smart Cities. Here, we implement a federated learning approach, where the process of learning is made in a distributed fashion. The use of blockchain in turn adds more security and resilience to smart city applications. The security analysis proves that the proposed approach offers comparatively better performance and remains more resistant to various security threats and vulnerabilities.

Original language	English
Title of host publication	Proceedings of ICACTCE'23—The International Conference on Advances in Communication Technology and Computer Engineering - New Artificial Intelligence and the Internet of Things Based Perspective and Solutions
Editors	Celestine Iwendi, Zakaria Boulouard, Natalia Kryvinska
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	105-118
Number of pages	14
ISBN (Print)	9783031371639
DOIs	https://doi.org/10.1007/978-3-031-37164-6_9
State	Published - 2023
Externally published	Yes
Event	International Conference on Advances in Communication Technology and Computer Engineering, ICACTCE 2023 - Bolton, United Kingdom Duration: 24 Feb 2023 → 25 Feb 2023

Publication series

Name	Lecture Notes in Networks and Systems
Volume	735 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Advances in Communication Technology and Computer Engineering, ICACTCE 2023
Country/Territory	United Kingdom
City	Bolton
Period	24/02/23 → 25/02/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Blockchain
Federated learning
IOT
Secure data sharing
Smart city

Access to Document

10.1007/978-3-031-37164-6_9

Cite this

Hai, T., Wang, D., Seetharaman, T., Amelesh, M., Sreejith, P. M., Sharma, V., Ibeke, E., & Liu, H. (2023). A Novel & Innovative Blockchain-Empowered Federated Learning Approach for Secure Data Sharing in Smart City Applications. In C. Iwendi, Z. Boulouard, & N. Kryvinska (Eds.), Proceedings of ICACTCE'23—The International Conference on Advances in Communication Technology and Computer Engineering - New Artificial Intelligence and the Internet of Things Based Perspective and Solutions (pp. 105-118). (Lecture Notes in Networks and Systems; Vol. 735 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-37164-6_9

Hai, Tao ; Wang, Dan ; Seetharaman, Tamizharasi et al. / A Novel & Innovative Blockchain-Empowered Federated Learning Approach for Secure Data Sharing in Smart City Applications. Proceedings of ICACTCE'23—The International Conference on Advances in Communication Technology and Computer Engineering - New Artificial Intelligence and the Internet of Things Based Perspective and Solutions. editor / Celestine Iwendi ; Zakaria Boulouard ; Natalia Kryvinska. Springer Science and Business Media Deutschland GmbH, 2023. pp. 105-118 (Lecture Notes in Networks and Systems).

@inproceedings{a82f3ebe564348a58a904a298f50843d,

title = "A Novel \& Innovative Blockchain-Empowered Federated Learning Approach for Secure Data Sharing in Smart City Applications",

abstract = "The very existence of smart cities forms the stepping stone in the evolution of many technological advancements in the future era. While smart cities have already grown in their way, the tremendous amount of data generated from them paves the way for new perspectives of development. This is because security and privacy remain to be the major constraint across smart city applications. Further, smart city applications such as smart homes, smart transportation, and smart healthcare are generating a huge amount of data every day and it is often complex to collect and manage all the data together at a single location. To address these constraints, this paper presents a novel and innovative blockchain-assisted federated learning approach for secure data sharing in IoT Smart Cities. Here, we implement a federated learning approach, where the process of learning is made in a distributed fashion. The use of blockchain in turn adds more security and resilience to smart city applications. The security analysis proves that the proposed approach offers comparatively better performance and remains more resistant to various security threats and vulnerabilities.",

keywords = "Blockchain, Federated learning, IOT, Secure data sharing, Smart city",

author = "Tao Hai and Dan Wang and Tamizharasi Seetharaman and M. Amelesh and Sreejith, \{P. M.\} and Vandana Sharma and Ebuka Ibeke and Hong Liu",

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Hai, T, Wang, D, Seetharaman, T, Amelesh, M, Sreejith, PM, Sharma, V, Ibeke, E & Liu, H 2023, A Novel & Innovative Blockchain-Empowered Federated Learning Approach for Secure Data Sharing in Smart City Applications. in C Iwendi, Z Boulouard & N Kryvinska (eds), Proceedings of ICACTCE'23—The International Conference on Advances in Communication Technology and Computer Engineering - New Artificial Intelligence and the Internet of Things Based Perspective and Solutions. Lecture Notes in Networks and Systems, vol. 735 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 105-118, International Conference on Advances in Communication Technology and Computer Engineering, ICACTCE 2023, Bolton, United Kingdom, 24/02/23. https://doi.org/10.1007/978-3-031-37164-6_9

A Novel & Innovative Blockchain-Empowered Federated Learning Approach for Secure Data Sharing in Smart City Applications. / Hai, Tao; Wang, Dan; Seetharaman, Tamizharasi et al.
Proceedings of ICACTCE'23—The International Conference on Advances in Communication Technology and Computer Engineering - New Artificial Intelligence and the Internet of Things Based Perspective and Solutions. ed. / Celestine Iwendi; Zakaria Boulouard; Natalia Kryvinska. Springer Science and Business Media Deutschland GmbH, 2023. p. 105-118 (Lecture Notes in Networks and Systems; Vol. 735 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Hai, Tao

AU - Wang, Dan

AU - Seetharaman, Tamizharasi

AU - Amelesh, M.

AU - Sreejith, P. M.

AU - Sharma, Vandana

AU - Ibeke, Ebuka

AU - Liu, Hong

PY - 2023

Y1 - 2023

N2 - The very existence of smart cities forms the stepping stone in the evolution of many technological advancements in the future era. While smart cities have already grown in their way, the tremendous amount of data generated from them paves the way for new perspectives of development. This is because security and privacy remain to be the major constraint across smart city applications. Further, smart city applications such as smart homes, smart transportation, and smart healthcare are generating a huge amount of data every day and it is often complex to collect and manage all the data together at a single location. To address these constraints, this paper presents a novel and innovative blockchain-assisted federated learning approach for secure data sharing in IoT Smart Cities. Here, we implement a federated learning approach, where the process of learning is made in a distributed fashion. The use of blockchain in turn adds more security and resilience to smart city applications. The security analysis proves that the proposed approach offers comparatively better performance and remains more resistant to various security threats and vulnerabilities.

AB - The very existence of smart cities forms the stepping stone in the evolution of many technological advancements in the future era. While smart cities have already grown in their way, the tremendous amount of data generated from them paves the way for new perspectives of development. This is because security and privacy remain to be the major constraint across smart city applications. Further, smart city applications such as smart homes, smart transportation, and smart healthcare are generating a huge amount of data every day and it is often complex to collect and manage all the data together at a single location. To address these constraints, this paper presents a novel and innovative blockchain-assisted federated learning approach for secure data sharing in IoT Smart Cities. Here, we implement a federated learning approach, where the process of learning is made in a distributed fashion. The use of blockchain in turn adds more security and resilience to smart city applications. The security analysis proves that the proposed approach offers comparatively better performance and remains more resistant to various security threats and vulnerabilities.

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KW - Smart city

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AN - SCOPUS:85174542288

SN - 9783031371639

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Hai T, Wang D, Seetharaman T, Amelesh M, Sreejith PM, Sharma V et al. A Novel & Innovative Blockchain-Empowered Federated Learning Approach for Secure Data Sharing in Smart City Applications. In Iwendi C, Boulouard Z, Kryvinska N, editors, Proceedings of ICACTCE'23—The International Conference on Advances in Communication Technology and Computer Engineering - New Artificial Intelligence and the Internet of Things Based Perspective and Solutions. Springer Science and Business Media Deutschland GmbH. 2023. p. 105-118. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-37164-6_9

A Novel & Innovative Blockchain-Empowered Federated Learning Approach for Secure Data Sharing in Smart City Applications

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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