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Cited by 50Vehicular Ad Hoc Networks (VANETs)Blockchain Technology Applications and SecurityNetwork Security and Intrusion Detection

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

BDTwin: An Integrated Framework for Enhancing Security and Privacy in Cybertwin-Driven Automotive Industrial Internet of Things

Kumar, Randhir, Kumar, Prabhat, Tripathi, Rakesh, Gupta, Govind P., Garg, Sahil, Hassan, Mohammad Mehedi·2022·IEEE Internet of Things Journal
DOI 10.1109/jiot.2021.3122021
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Abstract

The rapid development of the automotive Industrial Internet of Things requires secure networking infrastructure toward digitalization. Cybertwin (CT) is a next-generation networking architecture that serves as a communication, and digital asset owner, and can make the Vehicle-to-Everything (V2X) network flexible and secure. However, CT itself can publish end users’ digital assets to other entities as a service, making data security and privacy major obstacles in the realization of V2X applications. Motivated from the aforementioned discussion, this article presents BDTwin, a blockchain and deep-learning-based integrated framework to enhance security and privacy in CT-driven V2X applications. Specifically, a blockchain scheme is designed to ensure secure communication among vehicles, roadside units, CT-edge server, and cloud server using a smart contract-based enhance-Proof-of-Work (ePoW) and Zero Knowledge Proof (ZKP)-based verification process. Smart contracts are used to enforce rules and regulations that govern the behavior of V2X entities in a nondeniable and automated manner. In a deep-learning scheme, an autoregressive-deep variational autoencoder model is combined with attention-based bidirectional long short-term memory (A-BLSTM) for automatic feature extraction and attack detection by analyzing CT-edge servers data in a V2X environment. Security analysis and experimental results using two different sources, ToN-IoT and CICIDS-2017 show the superiority of the proposed…

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Crossref · 10.1109/jiot.2021.3122021

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  • The transport layer of the IoT includes the internet, mobile networks, and some nonmainstream professional networks, such as telecommunications networks and power carriers.

    “The transport layer of the IoT includes the internet, mobile networks, and some nonmainstream professional networks, such as telecommunications networks and power carriers [15].”

    From A Survey of IoT Privacy Security: Architecture, Technology, Challenges, and Trends (2024) · cites this paper as [15]

Citations

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Research works printed but not linked: 37

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Metadata

Authors
Kumar, R., Kumar, P., Tripathi, R., Gupta, G. P., Garg, S., & Hassan, M. M.
Affiliations
  • National Institute of Technology Raipur (IN)
  • École de Technologie Supérieure (CA)
  • King Saud University (SA)
ORCID
Venue
IEEE Internet of Things Journal
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2022-09-15
Volume
9
Issue
18
Pages
17110-17119
ISSN
  • 2327-4662 (ISSN-L)
  • 2372-2541
DOI
10.1109/jiot.2021.3122021
OpenAlex
W4205548770
Cited by
50
References
1
Citations by year
2025: 9 · 2024: 14 · 2023: 15 · 2022: 12
FWCI
3.02
Type
journal article
Language
en
Open access
closed
Licence
Locations
IEEE Internet of Things Journal (publishedVersion)
Funders
King Saud University, Riyadh, Saudi Arabia, through the Researchers Supporting Project (RSP-2021/18)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
Keywords
vehicle-to-everything communication, blockchain, smart contracts, zero-knowledge proofs, privacy preservation, attack detection, variational autoencoder, bidirectional LSTM, roadside units

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