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Blockchain and Machine Learning for IoT: Security and Privacy Challenges
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Blockchain and Machine Learning for IoT: Security and Privacy Challenges

A special issue of Network (ISSN 2673-8732).

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 24778

Special Issue Editors

Dr. Michele Mastroianni

E-Mail Website
Guest Editor
Department of Computer Science, University of Salerno, 84084 Fisciano, Italy
Interests: security and privacy; computer modeling and simulation; information systems; computer networks
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Francesco Palmieri

E-Mail Website
Guest Editor
Department of Computer Science, University of Salerno, Fisciano, Italy
Interests: networking; network security; distributed computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The pervasiveness of IoT technologies in a variety of fields is changing our lives. Industry, agriculture, health, and even personal life are experiencing a revolution in the way data are collected, communicated, processed, and stored. In recent years, two other technologies have begun to be used in synergy with IoT: Blockchain, which has changed the way data are stored, and machine learning, which has changed the way data are processed. With these premises in mind, it is desirable for researchers to focus their attention not just on the performance and features of the new systems but also on the new security and privacy issues related to this revolution. 

This Special Issue invites researchers to contribute with original contributions, case studies, and reviews that address all new challenges due to the use of IoT in synergy with blockchain systems and/or machine learning techniques.

The topics relevant for this Special Issue include (but are not limited to):

  • Security and privacy in blockchain technology for IoT;
  • Intelligent systems for fraud detection and forensics in blockchain environments;
  • Innovative architectures and protocols for safe blockchain application in IoT;
  • Blockchain and trust management;
  • Blockchain-based solutions for IoT security;
  • Novel machine learning and data science methods for IoT security;
  • Generative adversarial networks (GAN) in IoT security;
  • Architectures and protocols for scalable, secure, robust, and privacy enhancing IoT;
  • Privacy preservation in IoT;
  • Vulnerability analysis, threat modeling, and risk assessment in IoT;
  • Intrusion detection for IoT;
  • Novel security architectures, protocols, or applications for IoT.

This is a joint special issue with Electronics.

Dr. Michele Mastroianni
Prof. Dr. Francesco Palmieri
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. Network is an international peer-reviewed open access quarterly 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 1000 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
  • Machine Learning
  • IoT
  • Security
  • Privacy
  • Risk Analysis

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Published Papers (3 papers)

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Research

27 pages, 721 KiB  
Article
IoT and Blockchain Integration: Applications, Opportunities, and Challenges
by Naresh Adhikari and Mahalingam Ramkumar
Network 2023, 3(1), 115-141; https://doi.org/10.3390/network3010006 - 24 Jan 2023
Cited by 16 | Viewed by 7376
Abstract
During the recent decade, two variants of evolving computing networks have augmented the Internet: (i) The Internet of Things (IoT) and (ii) Blockchain Network(s) (BCNs). The IoT is a network of heterogeneous digital devices embedded with sensors and software for various automation and [...] Read more.
During the recent decade, two variants of evolving computing networks have augmented the Internet: (i) The Internet of Things (IoT) and (ii) Blockchain Network(s) (BCNs). The IoT is a network of heterogeneous digital devices embedded with sensors and software for various automation and monitoring purposes. A Blockchain Network is a broadcast network of computing nodes provisioned for validating digital transactions and recording the “well-formed” transactions in a unique data storage called a blockchain ledger. The power of a blockchain network is that (ideally) every node maintains its own copy of the ledger and takes part in validating the transactions. Integrating IoT and BCNs brings promising applications in many areas, including education, health, finance, agriculture, industry, and the environment. However, the complex, dynamic and heterogeneous computing and communication needs of IoT technologies, optionally integrated by blockchain technologies (if mandated), draw several challenges on scaling, interoperability, and security goals. In recent years, numerous models integrating IoT with blockchain networks have been proposed, tested, and deployed for businesses. Numerous studies are underway to uncover the applications of IoT and Blockchain technology. However, a close look reveals that very few applications successfully cater to the security needs of an enterprise. Needless to say, it makes less sense to integrate blockchain technology with an existing IoT that can serve the security need of an enterprise. In this article, we investigate several frameworks for IoT operations, the applicability of integrating them with blockchain technology, and due security considerations that the security personnel must make during the deployment and operations of IoT and BCN. Furthermore, we discuss the underlying security concerns and recommendations for blockchain-integrated IoT networks. Full article
(This article belongs to the Special Issue Blockchain and Machine Learning for IoT: Security and Privacy Challenges)
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22 pages, 438 KiB  
Article
Privacy-Aware Access Protocols for MEC Applications in 5G
by Gizem Akman, Philip Ginzboorg and Valtteri Niemi
Network 2022, 2(2), 203-224; https://doi.org/10.3390/network2020014 - 1 Apr 2022
Cited by 2 | Viewed by 2974
Abstract
Multi-access edge computing (MEC) is one of the emerging key technologies in fifth generation (5G) mobile networks, providing reduced end-to-end latency for applications and reduced load in the transport network. This paper proposes mechanisms to enhance user privacy in MEC within 5G. We [...] Read more.
Multi-access edge computing (MEC) is one of the emerging key technologies in fifth generation (5G) mobile networks, providing reduced end-to-end latency for applications and reduced load in the transport network. This paper proposes mechanisms to enhance user privacy in MEC within 5G. We consider a basic MEC usage scenario, where the user accesses an application hosted in the MEC platform via the radio access network of the mobile network operator (MNO). First, we create a system model based on this scenario. Second, we define the adversary model and give the list of privacy requirements for this system model. We also analyze the impact on user privacy when some of the parties in our model share information that is not strictly needed for providing the service. Third, we introduce a privacy-aware access protocol for the system model and analyze this protocol against the privacy requirements. Full article
(This article belongs to the Special Issue Blockchain and Machine Learning for IoT: Security and Privacy Challenges)
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15 pages, 2066 KiB  
Article
BloodChain: A Blood Donation Network Managed by Blockchain Technologies
by Hai Trieu Le, Tran Thanh Lam Nguyen, Tuan Anh Nguyen, Xuan Son Ha and Nghia Duong-Trung
Network 2022, 2(1), 21-35; https://doi.org/10.3390/network2010002 - 13 Jan 2022
Cited by 40 | Viewed by 11513
Abstract
Due to the rapid change of population structure, leading to lower birth rates and quick aging rates, the demand for blood supply is increasing significantly. In most countries, blood quality and origin are managed by blood management information systems, such as national authorities. [...] Read more.
Due to the rapid change of population structure, leading to lower birth rates and quick aging rates, the demand for blood supply is increasing significantly. In most countries, blood quality and origin are managed by blood management information systems, such as national authorities. Nevertheless, the traditional system has limitations in this field, such as a lack of detailed blood information, making it challenging to manage blood quality, supply, and demand. Hence, to solve these issues, this paper proposes a blockchain-based system called BloodChain, an improved system to support blood information management, providing more detailed information about blood, such as blood consumption and disposal. BloodChain exploits private blockchain techniques with a limited number of relatively fast and reliable participants, making them suitable for B2B (Business to Business) transactions. In this paper, we also develop a proposed system based on the architecture of Hyperledger Fabric. The evaluation of BloodChain is performed in several scenarios to prove our proposed model’s effectiveness. Full article
(This article belongs to the Special Issue Blockchain and Machine Learning for IoT: Security and Privacy Challenges)
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