Emerging Topics in Cybersecurity: Challenges and Solutions

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (15 January 2024) | Viewed by 5324

Special Issue Editors

Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80131 Naples, Italy
Interests: cloud security; IoT security; security service level agreements; security evaluation and security assessment; moving target defense
Special Issues, Collections and Topics in MDPI journals
Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80131 Naples, Italy
Interests: hardware security; IoT security; security in safety-critical systems; approximate computing and embedded systems based on the FPGA technology

Special Issue Information

Dear Colleagues,

Computing systems are becoming more and more pervasive in our everyday lives; they are spreading across a variety of technological and administrative domains, and their heterogeneity is continuously increasing.  Indeed, cloud infrastructures are used to offload personal devices, modern wireless connectivity allows for ubiquitous mobility, and low-power communications and edge/fog computing enable us to integrate cyber–physical systems in our daily routines.

These technologies have made it possible to originate and capture massive amounts of data, allowing for advantages and new services in numerous fields, e.g., to enhance the efficiency of healthcare management, infrastructure such as power distribution networks, city traffic management, crisis response, disaster resilience, and emergency management.

Additionally, such technologies and systems necessitate the sharing of data—that might include sensitive data—between many organizations.

Billions of heterogeneous systems that continuously send and receive data packets over the network, and technological and functional boundaries of software platforms that become more and more vague and aleatory, make the managing of such computing systems the most enduring challenge. As the complexity of the grid increases, the chances of faults also increases: even one single sensor transmitting faulty data can destabilize the whole functionality of the system.

Indeed, confidentiality, integrity, and availability properties are continuously and severely jeopardized at all levels due to the huge attack surface and due to new day-by-day designed cyberattacks targeting customers accessing the networks, communication infrastructures, and edge devices, while even targeting the people managing these computing systems.

Cybersecurity, hence, becomes a key element in the security and stability of computing systems since it is not only required for smart grids and smart cities, but also for traditional., i.e., non-smart, systems.

This Special Issue is intended to provide an opportunity to discuss and share what relates to the challenges that are still open, and the direction toward which research efforts are headed, as well as direct concrete experiences aimed at advancing the state-of-the-art methodologies and approaches for cybersecurity. In this context, we intend to select works covering one or more of the following topics:

  • Confidentiality, integrity and privacy for public, private, and hybrid clouds;
  • Emerging problems and recent trends in the field of IoT, fog, and edge computing security;
  • Attack detection and mitigation techniques and strategies;
  • Secure development methodologies;
  • Secure and trustworthy IoT applications;
  • Distributed architectures in support of IoT security;
  • Models and technologies for security management, configuration, and accounting;
  • Model-based analysis and security assessment.

Dr. Alessandra De Benedictis
Dr. Salvatore Barone
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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

  • edge/fog/cloud-distributed computing for IoT
  • IoT data privacy
  • cloud security

Published Papers (4 papers)

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Research

24 pages, 5641 KiB  
Article
Enhancing Security for IoT-Based Smart Renewable Energy Remote Monitoring Systems
by Alexandre Rekeraho, Daniel Tudor Cotfas, Petru Adrian Cotfas, Emmanuel Tuyishime, Titus Constantin Balan and Rebecca Acheampong
Electronics 2024, 13(4), 756; https://doi.org/10.3390/electronics13040756 - 13 Feb 2024
Viewed by 705
Abstract
Renewable energy is an essential solution for addressing climate change, providing sustainable options that are vital for a more environmentally friendly future. Integrating information technology (IT) into renewable energy systems has driven remarkable progress, enhanced efficiency, and enabled remote monitoring. Nevertheless, integrating IT [...] Read more.
Renewable energy is an essential solution for addressing climate change, providing sustainable options that are vital for a more environmentally friendly future. Integrating information technology (IT) into renewable energy systems has driven remarkable progress, enhanced efficiency, and enabled remote monitoring. Nevertheless, integrating IT into these systems dramatically increases their vulnerability to cyber threats and potential attacks. This study thoroughly investigates the enhancement of security measures in an IoT-based solar energy remote monitoring system. The research integrates advanced technologies, including Advanced Encryption Standard (AES), myRIO board, and NI’s SystemLink Cloud platform, to enhance data security in smart solar energy monitoring systems. Emphasizing AES encryption ensures secure information exchange between the myRIO board and the computer. NI’s SystemLink Cloud offers a user-friendly interface for real-time monitoring of critical solar system parameters, supported by robust security measures such as HTTPS encryption and access control. This study sets higher data protection standards in smart energy systems by promoting advanced encryption and secure cloud infrastructures. The approach involves seamlessly integrating renewable energy sources with IT innovations while prioritizing proactive measures to strengthen solar energy system security. Full article
(This article belongs to the Special Issue Emerging Topics in Cybersecurity: Challenges and Solutions)
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18 pages, 1803 KiB  
Article
MRAM Devices to Design Ternary Addressable Physically Unclonable Functions
by Manuel Aguilar Rios, Mahafujul Alam and Bertrand Cambou
Electronics 2023, 12(15), 3308; https://doi.org/10.3390/electronics12153308 - 02 Aug 2023
Viewed by 756
Abstract
We introduce a novel approach to constructing ternary addressable physically unclonable functions (TAPUFs) using magnetoresistive random-access memory (MRAM) devices. TAPUFs use three states (1, 0, and X) to track unstable cells. The proposed TAPUF leverages the resistance properties of MRAM cells to produce [...] Read more.
We introduce a novel approach to constructing ternary addressable physically unclonable functions (TAPUFs) using magnetoresistive random-access memory (MRAM) devices. TAPUFs use three states (1, 0, and X) to track unstable cells. The proposed TAPUF leverages the resistance properties of MRAM cells to produce unique digital fingerprints that can be effectively utilized in cryptographic protocols. We exploit the cell-to-cell variations in resistance values to generate reliable cryptographic keys and true random numbers, which can add protection against certain attacks. To evaluate the performance of the TAPUF, various tests were conducted, including assessments of inter-cell to intra-cell variation, inter-distance, bit error rate (BER), and temperature variation. These experiments were conducted using a low-power client device to replicate practical scenarios. The obtained results demonstrate that the proposed TAPUF exhibits exceptional scalability, energy efficiency, and reliability. Full article
(This article belongs to the Special Issue Emerging Topics in Cybersecurity: Challenges and Solutions)
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21 pages, 11923 KiB  
Article
DRnet: Dynamic Retraining for Malicious Traffic Small-Sample Incremental Learning
by Ruonan Wang, Jinlong Fei, Rongkai Zhang, Maohua Guo, Zan Qi and Xue Li
Electronics 2023, 12(12), 2668; https://doi.org/10.3390/electronics12122668 - 14 Jun 2023
Viewed by 780
Abstract
Deep learning has achieved good classification results in the field of traffic classification in recent years due to its good feature representation ability. However, the existing traffic classification technology cannot meet the requirements for the incremental learning of tasks in online scenarios. In [...] Read more.
Deep learning has achieved good classification results in the field of traffic classification in recent years due to its good feature representation ability. However, the existing traffic classification technology cannot meet the requirements for the incremental learning of tasks in online scenarios. In addition, due to the high concealment and fast update speed of malicious traffic, the number of labeled samples that can be captured is scarce, and small samples cannot drive neural network training, resulting in poor performance of the classification model. Therefore, this paper proposes an incremental learning method for small-sample malicious traffic classification. The method uses the pruning strategy to find the redundant network structure and dynamically allocates redundant neurons for training based on the proposed measurement method according to the difficulty of the new class. This enables the network to perform incremental learning without excessively consuming storage and computing resources, and reasonable allocation improves the classification accuracy of new classes. At the same time, through the knowledge transfer method, the model can reduce the catastrophic forgetting of the old class, relieve the pressure of training large parameters with small-sample data, and improve the model classification performance. Experiments involving multiple datasets and settings show that our method is superior to the established baseline in terms of classification accuracy, consuming 50% less memory. Full article
(This article belongs to the Special Issue Emerging Topics in Cybersecurity: Challenges and Solutions)
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15 pages, 2938 KiB  
Article
Development of a Platform for Learning Cybersecurity Using Capturing the Flag Competitions
by Iván Ortiz-Garces, Rommel Gutierrez, David Guerra, Santiago Sanchez-Viteri and William Villegas-Ch.
Electronics 2023, 12(7), 1753; https://doi.org/10.3390/electronics12071753 - 06 Apr 2023
Viewed by 2326
Abstract
Currently, cybersecurity is a topic of great importance for society. With the increase in the use of technology and the digitization of many activities, the number of cyber threats to which individuals and organizations are exposed has increased. In addition, the COVID-19 pandemic [...] Read more.
Currently, cybersecurity is a topic of great importance for society. With the increase in the use of technology and the digitization of many activities, the number of cyber threats to which individuals and organizations are exposed has increased. In addition, the COVID-19 pandemic has accelerated the digitization of many processes, further increasing the risk of cyberattacks. One of the main causes of these problems is the lack of cyber security awareness, as many people and organizations do not have a proper understanding of cyber threats and the measures, they must take to protect themselves. As a solution to the lack of cybersecurity knowledge, this work proposes the development of a Capture the Flag platform for learning about cybersecurity. The objective is to provide a tool that allows the education of future professionals in this field and covers the existing demand for this type of specialist. The platform is made up of two sections, one for learning and the other for CTF. The first section allows teachers to contribute to the teaching of their students using challenges. The second section allows one to carry out competitions with effective results when acquiring knowledge and experience. The platform is evaluated using questionnaires and surveys to measure whether the platform fulfills its purpose. Full article
(This article belongs to the Special Issue Emerging Topics in Cybersecurity: Challenges and Solutions)
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