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Novel Approaches for Cybersecurity and Cyber Defense

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 30 April 2026 | Viewed by 790

Special Issue Editors


E-Mail Website
Guest Editor
Department of Computers and Cyber Security, Military Technical Academy “Ferdinand I”, 050141 Bucharest, Romania
Interests: cryptography; searchable encryption; homomorphic encryption; biometry; identity-based encryption

E-Mail Website
Guest Editor
Department of Computers and Cyber Security, Military Technical Academy “Ferdinand I”, 050141 Bucharest, Romania
Interests: cybersecurity; cryptography; IoT; post-quantum cryptography

Special Issue Information

Dear Colleagues,

The rapid expansion of interconnected systems, ranging from essential infrastructure to consumer Internet of Things (IoT) devices, has expanded the scope of cyberspace. Advancements in 5G communication, edge computing, cloud-native services, and Artificial Intelligence (AI) automation have made digital ecosystems more complex and flexible. These innovations enhance operational efficiency and promote innovation, but they also significantly increase the attack surface, making systems vulnerable to more advanced cyber threats such as Advanced Persistent Threats (APTs), zero-day exploits, ransomware, and AI-powered intrusions.

Cybersecurity and cyber defense now face the critical challenge of protecting heterogeneous systems against an increasing range of risks, from data breaches and ransomware to AI-generated attacks and supply chain exploits. The limitations of traditional defense strategies, often reactive and perimeter-based, have highlighted the need for proactive, intelligent, and resilient methods that can operate across dynamic, interconnected environments.

This Special Issue seeks to present novel methodologies, technologies, and frameworks that address emerging challenges in cybersecurity and cyber defense. We welcome high-quality submissions that provide theoretical advances, practical implementations, and interdisciplinary perspectives. Both academic research and industry-driven case studies are encouraged.

Topics of interest include, but are not limited to, the following:

  • AI and machine learning for threat detection, risk assessment, and response automation;
  • Secure architectures for IoT, edge, and cloud systems;
  • Blockchain and distributed ledger technologies in cybersecurity applications;
  • Zero Trust and adaptive access control models;
  • Quantum-resilient cryptographic protocols;
  • Cyber situational awareness and attack surface monitoring;
  • Digital forensics, malware analysis, and anomaly detection;
  • Security in critical infrastructures;
  • Privacy-preserving computation and secure data sharing;
  • Integration of human factors and socio-technical considerations in cyber defense.

This Special Issue aims to promote knowledge exchange between academia and industry and to support the development of next-generation cybersecurity solutions that are scalable, adaptive, and resilient in real-world scenarios.

Dr. Stefania Loredana Nita
Prof. Dr. Ion Bica
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 250 words) can be sent to the Editorial Office for assessment.

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. Applied Sciences 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 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

  • cybersecurity
  • cyber defense
  • threat detection
  • secure architectures
  • privacy-preserving technologies
  • blockchain security
  • AI in cybersecurity
  • zero trust
  • post-quantum cryptography
  • critical infrastructure protection

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Published Papers (3 papers)

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Research

16 pages, 471 KB  
Article
Neural Key Agreement Protocol with Extended Security
by Mihail-Iulian Pleşa, Marian Gheorghe and Florentin Ipate
Appl. Sci. 2025, 15(23), 12746; https://doi.org/10.3390/app152312746 - 2 Dec 2025
Abstract
Key agreement protocols based on neural synchronization with Tree Parity Machines (TPMs) offer promising security advantages: they do not rely on trapdoor functions, making them resistant to quantum attacks, and they avoid the need for specialized hardware required by quantum-based schemes. Nevertheless, these [...] Read more.
Key agreement protocols based on neural synchronization with Tree Parity Machines (TPMs) offer promising security advantages: they do not rely on trapdoor functions, making them resistant to quantum attacks, and they avoid the need for specialized hardware required by quantum-based schemes. Nevertheless, these protocols face a significant vulnerability: the large number of public message exchanges required for synchronization increases the risk that an attacker, acting as a Man-in-the-Middle, can successfully synchronize their own TPMs with those of the legitimate parties and ultimately recover the shared key. Motivated by the need to reduce this risk, we propose a novel probabilistic protocol that enables two parties to securely estimate the size of the shared key during intermediate steps, without revealing any key material. This estimation allows the protocol to terminate as soon as sufficient key material has been established, thereby reducing the number of synchronization rounds and limiting the opportunity for an attacker to synchronize. We integrate our estimation mechanism into a neural key agreement protocol and evaluate its performance and security, demonstrating improved efficiency and enhanced resistance to attacks compared to existing approaches. Full article
(This article belongs to the Special Issue Novel Approaches for Cybersecurity and Cyber Defense)
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35 pages, 979 KB  
Article
Standard-Compliant Blockchain Anchoring for Timestamp Tokens
by Andrei Brînzea, Răzvan-Andrei Leancă, Iulian Aciobăniței and Florin Pop
Appl. Sci. 2025, 15(23), 12722; https://doi.org/10.3390/app152312722 - 1 Dec 2025
Abstract
Traditional Time-Stamping Authorities provide reliable temporal evidence. However, they operate as single points of trust and do not supply a tamper-evident record of event ordering. This paper presents a standards-compliant extension that anchors each issued timestamp token to a blockchain ledger while preserving [...] Read more.
Traditional Time-Stamping Authorities provide reliable temporal evidence. However, they operate as single points of trust and do not supply a tamper-evident record of event ordering. This paper presents a standards-compliant extension that anchors each issued timestamp token to a blockchain ledger while preserving full compatibility with existing TSA clients. Our proposal is compliant with RFC 3161. The implementation uses an identifier in the token that is also included in the distributed ledger. Experiments were conducted on the Ethereum and Hyperledger Fabric networks. Our design allows for external verification of the existence and relative ordering of tokens without modifying the RFC-defined validation process. Experimental evaluation compares issuance latency, anchoring time, and transaction cost across both networks. Our work presents a practical and viable approach to enhancing trust in digital signature infrastructures by combining the regulatory reliability of qualified TSAs with the auditability and persistence of distributed ledgers. Full article
(This article belongs to the Special Issue Novel Approaches for Cybersecurity and Cyber Defense)
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19 pages, 1018 KB  
Article
Fractality and Percolation Sensitivity in Software Vulnerability Networks: A Study of CWE–CVE–CPE Relations
by Iulian Tiță, Mihai Cătălin Cujbă and Nicolae Țăpuș
Appl. Sci. 2025, 15(21), 11336; https://doi.org/10.3390/app152111336 - 22 Oct 2025
Viewed by 363
Abstract
Public CVE feeds add tens of thousands of entries each year, overwhelming patch-management capacity. We model the CWE–CVE–CPE triad and, for each CWE, build count-weighted product co-exposure graphs by projecting CVE–CPE links. Because native graphs are highly fragmented, we estimate graph-distance box-counting dimensions [...] Read more.
Public CVE feeds add tens of thousands of entries each year, overwhelming patch-management capacity. We model the CWE–CVE–CPE triad and, for each CWE, build count-weighted product co-exposure graphs by projecting CVE–CPE links. Because native graphs are highly fragmented, we estimate graph-distance box-counting dimensions component-wise on the fragmented graphs using greedy box covering on unweighted shortest paths, then assess significance on the largest component of reconnected graphs. Significance is evaluated against degree-preserving nulls, reporting null percentiles, a z-score–based p-value, and complementary KS checks. We further characterise meso-scale organisation via normalized rich-club coefficients and k-core structure. Additionally, we quantify percolation sensitivity on the reconnected graphs by contrasting targeted removals with random failures for budgets of 1%, 5%, 10%, and 20%. This quantification involves tracking changes in largest-component size, average shortest-path length on the LCC, and global efficiency, and an amplification factor at 10%. Our corpus covers the MITRE CWE Top 25; we report high-level summaries for all 25 and perform the deepest null-model and sensitivity analyses on a subset of 12 CWEs selected on the basis of CVE volume. This links self-similar topology on native fragments with rich-club/core organisation and disruption sensitivity on reconnections, yielding actionable, vendor/software-type-aware mitigation cues. Structural indices are used descriptively to surface topological hotspots within CWE-conditioned product networks and are interpreted alongside, not in place of, EPSS/KEV/CVSS severity metrics. Full article
(This article belongs to the Special Issue Novel Approaches for Cybersecurity and Cyber Defense)
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