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Advanced Security and Privacy Focused Blockchain-Based Sensor Networks, Architectures and Next Generation Communications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 3205

Special Issue Editors

Prof. Dr. Aniruddha Bhattacharjya

E-Mail Website
Guest Editor
1. Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
2. Founder Chairman and Executive Director, BCBRBAB Intercontinental Trading Solutions Private Limited, Kolkata 700084, India
Interests: applied cryptography and cryptanalysis (RSA and AES and related ciphers); end-to-end (E2E) secure communication, peer to peer (P2P) communication and security aspects; information systems efficiency; lightweight and security aspects; blockchain applications and security aspects and software testing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Shaohua Wan

E-Mail Website
Guest Editor
Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen 518110, China
Interests: deep learning; Internet of Things; edge computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will introduce the present state of the art and use cases of Blockchain-based sensor networks, systems, architectures and next-generation communications considering security and privacy aspects. Very specific use cases and practical implementations will form a special section. The security, efficiency and scalability of these architectures will be discussed. Articles regarding all types of emerging Blockchain-based architectures, sensor networks and next-generation communication systems will be included in this Special Issue. Topics include, but are not limited to:

  • Blockchain-based wireless sensor networks (WSNs) (BWSN);
  • Blockchain-based sensor data communication;
  • Blockchain-enabled IoT (BIoT) with security and privacy aspects;
  • Sensor tracking and traceability using blockchain-based supply chain management (SCM);
  • Blockchain-enabled sensor technology in wireless networks;
  • Blockchain and mobile wireless sensor networks;
  • Blockchain and distributed ledger solutions for data veracity and privacy in WSNs;
  • Improvement of security, reliability and trust in WSN through the use of Blockchain;
  • Consensus mechanism for wireless sensor networks (WSNs);
  • Blockchain, IoT, and WSNs;
  • Industrial Internet of Things (IIoT), Blockchain and smart contracts;
  • Blockchain for 6G-enabled network-based applications with a focus on security, privacy and efficiency;
  • Fog/Edge-integrated architecture in WSNs with blockchain with a focus on security, privacy and efficiency;
  • Blockchain in connected and autonomous vehicles;
  • Blockchain in edge and cloud computing;
  • Blockchain in next-generation communications and sensor networks;
  • Blockchain in crowdsourcing and crowdsensing;
  • Software-defined networking (SDN) for Blockchain;
  • Blockchain and data analytics;
  • AI-based edge computing over Blockchain;
  • Blockchain and beyond wireless technologies;
  • Secure storage and access in wireless sensor networks (WSNs) using Blockchain

Prof. Dr. Aniruddha Bhattacharjya
Prof. Dr. Shaohua Wan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • blockchain-based wireless sensor networks (BWSNs)
  • blockchain-enabled IoT (BIoT)
  • industrial Internet of Things (IIoT)
  • data veracity and privacy in wireless sensor networks (WSNs)
  • blockchain-based sensor data communication (BSDC)

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Published Papers (2 papers)

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Research

19 pages, 3741 KiB  
Article
Research on Network Security Protection Technology Based on P2AEDR in New Low-Voltage Control Scenarios for Power IoT and Other Blockchain-Based IoT Architectures
by Weiwei Miao, Xinjian Zhao, Nianzhe Li, Song Zhang, Qianmu Li and Xiaochao Li
Sensors 2024, 24(21), 6808; https://doi.org/10.3390/s24216808 - 23 Oct 2024
Viewed by 686
Abstract
In the construction of new power systems, the traditional network security protection mainly based on boundary protection belongs to static defense and still relies mainly on manual processing in vulnerability repair, threat response, etc. It is difficult to adapt to the security protection [...] Read more.
In the construction of new power systems, the traditional network security protection mainly based on boundary protection belongs to static defense and still relies mainly on manual processing in vulnerability repair, threat response, etc. It is difficult to adapt to the security protection needs in large-scale distributed new energy, third-party aggregation platforms, and flexible interaction scenarios with power grid enterprise systems. It is necessary to conduct research on dynamic security protection models for IoT and other Blockchain-based IoT architectures. This article proposes a network security comprehensive protection model P2AEDR based on different interaction modes of cloud–edge interaction and cloud–cloud interaction. Through continuous trust evaluation, dynamic access control, and other technologies, it strengthens the internal defense capabilities of power grid business, shifting from static protection as the core mode to a real-time intelligent perception and automated response mode, and ultimately achieving the goal of dynamic defense, meeting the security protection needs of large-scale controlled terminal access and third-party aggregation platforms. Meanwhile, this article proposes a dynamic trust evaluation algorithm based on deep learning, which protects the secure access and use of various resources in a more refined learning approach based on the interaction information monitored in the system. Through experimental verification of the dynamic trust evaluation algorithm, it is shown that the proposed model has good trust evaluation performance. Therefore, this research is beneficial for trustworthy Power IoT and other Blockchain-based IoT architectures. Full article
(This article belongs to the Special Issue Advanced Security and Privacy Focused Blockchain-Based Sensor Networks, Architectures and Next Generation Communications)
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20 pages, 1964 KiB  
Article
A Deep Learning-Based Method for Preventing Data Leakage in Electric Power Industrial Internet of Things Business Data Interactions
by Weiwei Miao, Xinjian Zhao, Yinzhao Zhang, Shi Chen, Xiaochao Li and Qianmu Li
Sensors 2024, 24(13), 4069; https://doi.org/10.3390/s24134069 - 22 Jun 2024
Viewed by 1076
Abstract
In the development of the Power Industry Internet of Things, the security of data interaction has always been an important challenge. In the power-based blockchain Industrial Internet of Things, node data interaction involves a large amount of sensitive data. In the current anti-leakage [...] Read more.
In the development of the Power Industry Internet of Things, the security of data interaction has always been an important challenge. In the power-based blockchain Industrial Internet of Things, node data interaction involves a large amount of sensitive data. In the current anti-leakage strategy for power business data interaction, regular expressions are used to identify sensitive data for matching. This approach is only suitable for simple structured data. For the processing of unstructured data, there is a lack of practical matching strategies. Therefore, this paper proposes a deep learning-based anti-leakage method for power business data interaction, aiming to ensure the security of power business data interaction between the State Grid business platform and third-party platforms. This method combines named entity recognition technologies and comprehensively uses regular expressions and the DeBERTa (Decoding-enhanced BERT with disentangled attention)-BiLSTM (Bidirectional Long Short-Term Memory)-CRF (Conditional Random Field) model. This method is based on the DeBERTa (Decoding-enhanced BERT with disentangled attention) model for pre-training feature extraction. It extracts sequence context semantic features through the BiLSTM, and finally obtains the global optimal through the CRF layer tag sequence. Sensitive data matching is performed on interactive structured and unstructured data to identify privacy-sensitive information in the power business. The experimental results show that the F1 score of the proposed method in this paper for identifying sensitive data entities using the CLUENER 2020 dataset reaches 81.26%, which can effectively prevent the risk of power business data leakage and provide innovative solutions for the power industry to ensure data security. Full article
(This article belongs to the Special Issue Advanced Security and Privacy Focused Blockchain-Based Sensor Networks, Architectures and Next Generation Communications)
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