Special Issue "Artificial Intelligence Applications in Next Generation Communication Infrastructures Security"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 2346

Special Issue Editors

Dr. George Hatzivasilis
E-Mail Website
Guest Editor
Institute of Computer Science, Foundation for Research and Technology–Hellas (FORTH), Vassilika Vouton, 70013 Heraklion, Greece
Interests: information and intelligent systems security; cyber-security training; Internet-of-Things (IoT); cyber-physical systems (CPS); SDN/NFV; big data analysis; block chaining and forensics; ambient intelligence; disaster mitigation planning
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Prof. Dr. Sotiris Ioannidis
E-Mail Website
Guest Editor
School of Electrical and Computer Engineering, Technical University of Crete, Campus Kounoupidiana, 73100 Chania, Crete, Greece
Interests: cybersecurity; trusted execution; reconfigurable hardware; artificial intelligence; systems security
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Dr. Konstantinos Fysarakis
E-Mail Website
Guest Editor
Innovation Department, Sphynx Technology Solutions AG, 6300 Zug, Switzerland
Interests: security; dependability and sustainability challenges in next generation networking infrastructures; various privacy and trust concerns in Internet of Things (IoT); pertinent security management issues
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Dr. Nikolaos Papadakis
E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71410 Estavromenos, Greece
Interests: databases; artificial intelligence; software engineering; semantic web; distributed algorithms; communication protocols; fault tolerance; multimedia databases; methods of automatic optimization of software; interactive verifier
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As increasingly more daily activities are digitalized, computer systems and their underlying communication networks are becoming decentralized and ubiquitous, with their attack surfaces being greatly increased. The management of security, privacy, and trust is becoming all the more challenging.

In this context, Artificial Intelligence (AI) and Machine Learning (ML) emerge as promising technologies in tackling these challenges. AI and ML have seen great progress in the last few years. Advanced, more accurate algorithms, more efficient implementations, and deployments on a wide range of applications have improved the performance and effectiveness of several traditional and novel computerized systems. As AI and ML capabilities are integrated into smart devices, they enable novel applications but also advanced cyber defenses. The latter now cover the whole cyber security lifecycle from training, analysis, and design, to the development of accurate forecasting, protection mechanisms, as well as incident response, mitigation, and restoration approaches.

Nevertheless, and in parallel to the above, several additional challenges will have to be addressed, stemming from the evolution of computing and communication infrastructure, including the shift to 5G networks: providing end-to-end protection and security/privacy properties, supporting (semi-)autonomous operation and self-configuration, fortifying trusted information and resource sharing, preserving the dependability of massively generated network traffic with heterogeneous particularities, offering fast identification of new threats and open vulnerabilities. Therefore, due to the sheer complexity of modern systems and networks that must be secured and the ever-increasing volumes of sophisticated cyber-attacks, it is becoming imperative to provide effective management of the associated cyber security risks in organizations and enterprises across the various vertical domains.

Motivated by the above, we invite submissions of full research and survey papers on topics related to AI, ML, Next Generation Communications and Cyber Security.

Dr. George Hatzivasilis
Prof. Dr. Sotiris Ioannidis
Dr. Konstantinos Fysarakis
Dr. Nikolaos Papadakis
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. Electronics 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 2000 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

  • AI-enhanced system analysis and design
  • asset management
  • control effectiveness
  • threat exposure
  • breach risk prediction
  • AI security by design
  • forecast
  • predictive intelligence for security and privacy management
  • malware analysis
  • bot identification
  • AI-based protection mechanisms
  • AI-driven defenses
  • secure and dependable autonomous systems
  • smart device security
  • AI-driven incident response
  • moving target defenses (MTDs)
  • reputation- and trust-based computing
  • novel AI applications
  • cloud-based AI
  • machine learning and blockchaining
  • 5G and novel IoT environments
  • COVID-19 impact on cyber security
  • cyber ranges and security training
  • leveraging AI for enhanced trust in vertical domains (e.g., smart agriculture, smart manufacturing, and healthcare)

Published Papers (2 papers)

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Research

Article
Detection of Security Attacks in Industrial IoT Networks: A Blockchain and Machine Learning Approach
Electronics 2021, 10(21), 2662; https://doi.org/10.3390/electronics10212662 - 30 Oct 2021
Cited by 3 | Viewed by 571
Abstract
Internet of Things (IoT) networks have been integrated into industrial infrastructure schemes, positioning themselves as devices that communicate highly classified information for the most critical companies of world nations. Currently, and in order to look for alternatives to mitigate this risk, solutions based [...] Read more.
Internet of Things (IoT) networks have been integrated into industrial infrastructure schemes, positioning themselves as devices that communicate highly classified information for the most critical companies of world nations. Currently, and in order to look for alternatives to mitigate this risk, solutions based on Blockchain algorithms and Machine Learning techniques have been implemented separately with the aim of mitigating potential threats in IIoT networks. In this paper, we sought to integrate the previous solutions to create an integral protection mechanism for IoT device networks, which would allow the identification of threats, activate secure information transfer mechanisms, and it would be adapted to the computational capabilities of industrial IoT. The proposed solution achieved the proposed objectives and is presented as a viable mechanism for detecting and containing intruders in an IoT network. In some cases, it overcomes traditional detection mechanisms such as an IDS. Full article
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Article
The Green Blockchains of Circular Economy
Electronics 2021, 10(16), 2008; https://doi.org/10.3390/electronics10162008 - 19 Aug 2021
Cited by 3 | Viewed by 864
Abstract
Eco-friendly systems are necessitated nowadays, as the global consumption is increasing. A data-driven aspect is prominent, involving the Internet of Things (IoT) as the main enabler of a Circular Economy (CE). Henceforth, IoT equipment records the system’s functionality, with machine learning (ML) optimizing [...] Read more.
Eco-friendly systems are necessitated nowadays, as the global consumption is increasing. A data-driven aspect is prominent, involving the Internet of Things (IoT) as the main enabler of a Circular Economy (CE). Henceforth, IoT equipment records the system’s functionality, with machine learning (ML) optimizing green computing operations. Entities exchange and reuse CE assets. Transparency is vital as the beneficiaries must track the assets’ history. This article proposes a framework where blockchaining administrates the cooperative vision of CE-IoT. For the core operation, the blockchain ledger records the changes in the assets’ states via smart contracts that implement the CE business logic and are lightweight, complying with the IoT requirements. Moreover, a federated learning approach is proposed, where computationally intensive ML tasks are distributed via a second contract type. Thus, “green-miners” devote their resources not only for making money, but also for optimizing operations of real-systems, which results in actual resource savings. Full article
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