Blockchain-Based Cryptography, Privacy-Preserving and Cybersecurity Systems

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

Deadline for manuscript submissions: 15 November 2024 | Viewed by 2029

Special Issue Editors


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Guest Editor
Department of Computer Engineering, Catholic University of Pusan, Busan 46252, Republic of Korea
Interests: security in network; convergence and operating system

E-Mail Website
Guest Editor
Department of Information Security Engineering, Joongbu University, Goyang City 10279, Republic of Korea
Interests: network security; information security consulting; digital forensic

Special Issue Information

Dear Colleagues,

Blockchain and privacy-preserving techniques can provide security guarantees for the construction of digital government and digital economy. Security infrastructure needs to be adapted to support all kinds of application environments, such as dynamic and rapid changes in network topology, intermittent connection, limited source terminals, low-latency demand, privacy protection in terms of the publisher's location, and subscription.

Blockchain is a public ledger that does not rely on a single source. Blockchain provides undeniability for users, but it disregards user data privacy, thus posing a need for a combined overview of the efforts of recent years to address both security and privacy issues in application systems.

In this Special Issue, we aim to focus on the following research areas: blockchain-based cryptography, privacy-preserving, and cybersecurity systems. The Special Issue aims to focus on data confidentiality protection, data access control, and private-preserving systems, with contradiction and unity between security, scalability, and efficiency. Additionally, we invite authors to submit their abstracts, modeling and exploring methods in terms of scalability authorization control over ciphertext aggregating, access, write and search, etc. The following items in particular will be considered: ciphertext confidentiality, forward security and backward security on dynamic privilege management, and resistance of collusion.

Technical Program Committee Member:

Name: Dr. Jiaoli Shi
Email: [email protected]
Affiliation: School of Computer and Big Data Science, Jiujiang University, Jiujiang 332005, China
Research Interests: Cloud security; ICN security; Data Security; Private-Persevering Computation; Blockchain in Future Network

Prof. Dr. Daesung Lee
Prof. Dr. Minsu Kim
Guest Editors

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Keywords

  • blockchain
  • privacy-preserving system
  • data confidentiality protection
  • data access control
  • dynamic privilege management
  • ciphertext search
  • cybersecurity

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Published Papers (2 papers)

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Research

34 pages, 2733 KiB  
Article
Assessing the Effectiveness of Cyber Domain Controls When Conducting Cybersecurity Audits: Insights from Higher Education Institutions in Canada
by Regner Sabillon, Juan Ramon Bermejo Higuera, Jeimy Cano, Javier Bermejo Higuera and Juan Antonio Sicilia Montalvo
Electronics 2024, 13(16), 3257; https://doi.org/10.3390/electronics13163257 - 16 Aug 2024
Viewed by 845
Abstract
This study validates a comprehensive cybersecurity audit model through empirical analysis in three higher education institutions in Canada. The research aims to enhance cybersecurity resilience by assessing the effectiveness of cybersecurity controls across diverse educational environments. Given the increasing frequency and sophistication of [...] Read more.
This study validates a comprehensive cybersecurity audit model through empirical analysis in three higher education institutions in Canada. The research aims to enhance cybersecurity resilience by assessing the effectiveness of cybersecurity controls across diverse educational environments. Given the increasing frequency and sophistication of cyberattacks targeting educational institutions, this research is essential to ensure the protection of sensitive academic and personal data. Data were collected through detailed audits involving system vulnerabilities, compliance with security policies, and incident response management at each institution. The findings underscore the importance of tailored cybersecurity strategies and continuous auditing to mitigate cyber risks in the Canadian higher education sector. This study contributes to the field by validating a versatile audit tool that can be adapted to various institutional contexts, promoting enhanced cybersecurity practices and evaluating the effectiveness of cybersecurity safeguards across the higher education sector in Canada. The results of the audit model validations provide the cybersecurity maturity rating of each institution. Further research is recommended to refine the model and explore its application in other industries and sectors. Full article
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29 pages, 9974 KiB  
Article
Benchmarking Android Malware Analysis Tools
by Javier Bermejo Higuera, Javier Morales Moreno, Juan Ramón Bermejo Higuera, Juan Antonio Sicilia Montalvo, Gustavo Javier Barreiro Martillo and Tomas Miguel Sureda Riera
Electronics 2024, 13(11), 2103; https://doi.org/10.3390/electronics13112103 - 28 May 2024
Viewed by 908
Abstract
Today, malware is arguably one of the biggest challenges organisations face from a cybersecurity standpoint, regardless of the types of devices used in the organisation. One of the most malware-attacked mobile operating systems today is Android. In response to this threat, this paper [...] Read more.
Today, malware is arguably one of the biggest challenges organisations face from a cybersecurity standpoint, regardless of the types of devices used in the organisation. One of the most malware-attacked mobile operating systems today is Android. In response to this threat, this paper presents research on the functionalities and performance of different malicious Android application package analysis tools, including one that uses machine learning techniques. In addition, it investigates how these tools streamline the detection, classification, and analysis of malicious Android Application Packages (APKs) for Android operating system devices. As a result of the research included in this article, it can be highlighted that the AndroPytool, a tool that uses machine learning (ML) techniques, obtained the best results with an accuracy of 0.986, so it can be affirmed that the tools that use artificial intelligence techniques used in this study are more efficient in terms of detection capacity. On the other hand, of the online tools analysed, Virustotal and Pithus obtained the best results. Based on the above, new approaches can be suggested in the specification, design, and development of new tools that help to analyse, from a cybersecurity point of view, the code of applications developed for this environment. Full article
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