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JCP
Special Issues
Cybersecurity Risk Prediction, Assessment and Management
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Cybersecurity Risk Prediction, Assessment and Management

A special issue of Journal of Cybersecurity and Privacy (ISSN 2624-800X). This special issue belongs to the section "Security Engineering & Applications".

Deadline for manuscript submissions: 30 July 2025 | Viewed by 71723

Special Issue Editors

Dr. Gahangir Hossain

E-Mail Website1 Website2
Guest Editor
Department of Information Science, University of North Texas, Canyon, TX 76203, USA
Interests: cybersecurity management; cyber forensics; IoT security; cloud security; risk management; authentication; cognitive cybersecurity algorithms
Dr. Ibrahim Lazrig

E-Mail Website
Guest Editor
Department of Computer Information Science, West Texas A&M University, Canyon, TX 79106, USA
Interests: privacy preserving probabilistic record linkage using locality sensitive hashes; privacy preserving record matching using automated semi-trusted broker
Dr. Murray Jennex

E-Mail Website
Guest Editor
Department of Computer Information Science, West Texas A&M University, Canyon, TX 79106, USA
Interests: knowledge management; cybersecurity; outsourcing, ecommerce, and crisis response

Special Issue Information

Dear Colleagues,

In the age of Industry 5.0, businesses rely more on information technology and information systems to conduct their operations. The landscape of digital risk threats grows, exposing technological industries to serious cyber-threats and vulnerabilities. Hence, research on cybersecurity risk prediction, assessment, and management are critical responsibilities, not only for information technology personnel but also for all people using information technology as the day-to-day business.

Cybersecurity risk prediction, assessment, and management are crucial parts of risk management plans and data protection initiatives. Cybersecurity risk prediction, assessments, and management assist industries or stakeholders in early prediction, forecasting, and warning of cyber-threats; in the comprehension of the identification, analysis, evaluation, countermeasures, monitoring and review; and in management, including strategic planning, investigating, deciding, and reporting; to reduce all types of cybersecurity risks. This Special Issue on “Cybersecurity Risk Prediction, Assessment and Management” calls for submissions from researchers applying information technology in their organization. Suggested topics of interest include but are not limited to:

  • Cybersecurity-risk-related human–computer interaction and algorithms;
  • Cybersecurity risk situation and context;
  • Cybersecurity risk identification;
  • Cybersecurity risk analysis;
  • Cybersecurity risk evaluation;
  • Cybersecurity risk treatment;
  • Cybersecurity monitoring and review;
  • Cybersecurity risk prediction an assessment algorithms;
  • Cybersecurity risk with blockchain;
  • Cybersecurity risk with social media;
  • Data mining for cybersecurity risk analysis;
  • Cyber-threat data visualization and pattern recognition;
  • Cybersecurity risk with context, environment, and situation;
  • Machine learning for automating cybersecurity risk analysis;
  • Intelligent agent systems for cybersecurity risk monitoring;
  • Multi-agent collaborative risk management;  
  • Critical cyberinfrastructure risk management.

Dr. Gahangir Hossain
Dr. Ibrahim Lazrig
Dr. Murray Jennex
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. Journal of Cybersecurity and Privacy 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.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

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17 pages, 2794 KiB  
Article
Security Operations Centers: Use Case Best Practices, Coverage, and Gap Analysis Based on MITRE Adversarial Tactics, Techniques, and Common Knowledge
by Samir Achraf Chamkar, Yassine Maleh and Noreddine Gherabi
J. Cybersecur. Priv. 2024, 4(4), 777-793; https://doi.org/10.3390/jcp4040036 - 25 Sep 2024
Viewed by 3637
Abstract
The rising frequency and complexity of cybersecurity threats necessitate robust monitoring and rapid response capabilities to safeguard digital assets effectively. As a result, many organizations are increasingly establishing Security Operations Centers (SOCs) to actively detect and respond to cybersecurity incidents. This paper addresses [...] Read more.
The rising frequency and complexity of cybersecurity threats necessitate robust monitoring and rapid response capabilities to safeguard digital assets effectively. As a result, many organizations are increasingly establishing Security Operations Centers (SOCs) to actively detect and respond to cybersecurity incidents. This paper addresses the intricate process of setting up a SOC, emphasizing the need for careful planning, substantial resources, and a strategic approach. This study outlines the essential steps involved in defining the SOC’s objectives and scope, selecting appropriate technologies, recruiting skilled cybersecurity professionals, and developing processes throughout the SOC lifecycle. This paper aims to provide a comprehensive understanding of the SOC’s threat detection capabilities and use cases. It also highlights the importance of choosing technologies that integrate seamlessly with existing IT infrastructure to ensure broad coverage of SOC activities. Furthermore, this study offers actionable insights for organizations looking to enhance their SOC capabilities, including a technical overview of SOC use case coverage and a gap assessment of detection rules. This assessment is based on an alignment with the MITRE ATT&CK framework and an analysis of events generated by the company’s existing IT devices and products. The findings from this research elucidate the indispensable role that SOCs play in bolstering organizational cybersecurity and resilience. Full article
(This article belongs to the Special Issue Cybersecurity Risk Prediction, Assessment and Management)
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28 pages, 5949 KiB  
Article
Business Email Compromise (BEC) Attacks: Threats, Vulnerabilities and Countermeasures—A Perspective on the Greek Landscape
by Anastasios Papathanasiou, George Liontos, Vasiliki Liagkou and Euripidis Glavas
J. Cybersecur. Priv. 2023, 3(3), 610-637; https://doi.org/10.3390/jcp3030029 - 2 Sep 2023
Cited by 8 | Viewed by 10053
Abstract
Business Email Compromise (BEC) attacks have emerged as serious threats to organizations in recent years, exploiting social engineering and malware to dupe victims into divulging confidential information and executing fraudulent transactions. This paper provides a comprehensive review of BEC attacks, including their principles, [...] Read more.
Business Email Compromise (BEC) attacks have emerged as serious threats to organizations in recent years, exploiting social engineering and malware to dupe victims into divulging confidential information and executing fraudulent transactions. This paper provides a comprehensive review of BEC attacks, including their principles, techniques, and impacts on enterprises. In light of the rising tide of BEC attacks globally and their significant financial impact on business, it is crucial to understand their modus operandi and adopt proactive measures to protect sensitive information and prevent financial losses. This study offers valuable recommendations and insights for organizations seeking to enhance their cybersecurity posture and mitigate the risks associated with BEC attacks. Moreover, we analyze the Greek landscape of cyberattacks, focusing on the existing regulatory framework and the measures taken to prevent and respond to cybercrime in accordance with the NIS Directives of the EU. By examining the Greek landscape, we gain insights into the effectiveness of countermeasures in this region, as well as the challenges and opportunities for improving cybersecurity practices. Full article
(This article belongs to the Special Issue Cybersecurity Risk Prediction, Assessment and Management)
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Review

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51 pages, 1137 KiB  
Review
Autonomous Vehicles: Sophisticated Attacks, Safety Issues, Challenges, Open Topics, Blockchain, and Future Directions
by Anastasios Giannaros, Aristeidis Karras, Leonidas Theodorakopoulos, Christos Karras, Panagiotis Kranias, Nikolaos Schizas, Gerasimos Kalogeratos and Dimitrios Tsolis
J. Cybersecur. Priv. 2023, 3(3), 493-543; https://doi.org/10.3390/jcp3030025 - 5 Aug 2023
Cited by 55 | Viewed by 56493
Abstract
Autonomous vehicles (AVs), defined as vehicles capable of navigation and decision-making independent of human intervention, represent a revolutionary advancement in transportation technology. These vehicles operate by synthesizing an array of sophisticated technologies, including sensors, cameras, GPS, radar, light imaging detection and ranging (LiDAR), [...] Read more.
Autonomous vehicles (AVs), defined as vehicles capable of navigation and decision-making independent of human intervention, represent a revolutionary advancement in transportation technology. These vehicles operate by synthesizing an array of sophisticated technologies, including sensors, cameras, GPS, radar, light imaging detection and ranging (LiDAR), and advanced computing systems. These components work in concert to accurately perceive the vehicle’s environment, ensuring the capacity to make optimal decisions in real-time. At the heart of AV functionality lies the ability to facilitate intercommunication between vehicles and with critical road infrastructure—a characteristic that, while central to their efficacy, also renders them susceptible to cyber threats. The potential infiltration of these communication channels poses a severe threat, enabling the possibility of personal information theft or the introduction of malicious software that could compromise vehicle safety. This paper offers a comprehensive exploration of the current state of AV technology, particularly examining the intersection of autonomous vehicles and emotional intelligence. We delve into an extensive analysis of recent research on safety lapses and security vulnerabilities in autonomous vehicles, placing specific emphasis on the different types of cyber attacks to which they are susceptible. We further explore the various security solutions that have been proposed and implemented to address these threats. The discussion not only provides an overview of the existing challenges but also presents a pathway toward future research directions. This includes potential advancements in the AV field, the continued refinement of safety measures, and the development of more robust, resilient security mechanisms. Ultimately, this paper seeks to contribute to a deeper understanding of the safety and security landscape of autonomous vehicles, fostering discourse on the intricate balance between technological advancement and security in this rapidly evolving field. Full article
(This article belongs to the Special Issue Cybersecurity Risk Prediction, Assessment and Management)
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