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Applied Sciences
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Information Security: Threats and Attacks
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Information Security: Threats and Attacks

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

Deadline for manuscript submissions: 20 November 2026 | Viewed by 9480

Special Issue Editors

Dr. Yue Zhang

E-Mail Website
Guest Editor
Department of Computer Science, Drexel University, Philadelphia, PA, USA
Interests: program analysis; data security and privacy; mobile security; IoT security
Special Issues, Collections and Topics in MDPI journals
Dr. Bogdan Ghita

E-Mail Website
Guest Editor
Faculty of Science and Engineering, Plymouth University, Drake Circus, Plymouth PL4 8AA, UK
Interests: computer networks; wireless networks; network performance; network security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The ever-increasing reliance on digital technologies has been accompanied by a surge in cyber threats and sophisticated attack strategies targeting critical information infrastructures, businesses, and individuals. From ransomware and phishing attacks to advanced persistent threats and zero-day exploits, understanding and addressing the evolving threat landscape remains a cornerstone of information security research.

This Special Issue focuses on exploring the latest advances in identifying, analyzing, and mitigating threats and attacks in cyberspace. It aims to foster cutting-edge research and bring together innovative solutions to enhance the detection, prevention, and resilience of systems against diverse forms of malicious activities.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  1. Ransomware and extortion attacks;
  2. Web attacks, such as phishing and social engineering attacks;
  3. Advanced persistent threats (APTs);
  4. Zero-day exploits;
  5. Distributed denial of service (DDoS) attacks;
  6. Malware, including trojans, worms, and spyware;
  7. Insider threats and privilege abuse;
  8. IoT-specific attacks and vulnerabilities;
  9. Cryptographic attacks (e.g., side-channel and brute-force);
  10. Supply chain attacks;
  11. AI attacks.

Dr. Yue Zhang
Dr. Bogdan Ghita
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

  • attack exploiting
  • threats evaluation
  • attack and defense
  • attack and detection
  • vulnerability and attacks

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Published Papers (3 papers)

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Research

40 pages, 742 KB  
Article
Design-Space Mapping of Post-Quantum Cryptographic Artifact Transport on CAN-FD: A Discrete-Event Simulation Study
by Min-Woo Lee, Minjoo Sim, Siwoo Eum, Gyeongju Song and Hwajeong Seo
Appl. Sci. 2026, 16(8), 3705; https://doi.org/10.3390/app16083705 - 10 Apr 2026
Viewed by 185
Abstract
Post-quantum cryptography (PQC) artifacts are one to three orders of magnitude larger than their classical counterparts and must be segmented via ISO-TP across a shared CAN-FD bus while coexisting with periodic safety-critical traffic. No prior work has quantitatively mapped the transport-level feasibility of [...] Read more.
Post-quantum cryptography (PQC) artifacts are one to three orders of magnitude larger than their classical counterparts and must be segmented via ISO-TP across a shared CAN-FD bus while coexisting with periodic safety-critical traffic. No prior work has quantitatively mapped the transport-level feasibility of these artifacts under realistic multi-electronic control unit (ECU) contention. This paper presents a validated discrete-event simulator and evaluates 29 parameter sets from nine algorithm families—spanning the KpqC final portfolio, NIST FIPS 203–205 standards, and the draft FIPS 206—across 534 scenarios classified as feasible, borderline, or infeasible. Results show that key encapsulation mechanism (KEM) feasibility is scenario-dependent: domain scale and startup coordination dominate over algorithm choice, with 4-ECU staggered deployments feasible for all Level-1 candidates, while 16-ECU simultaneous startup is universally infeasible. For digital signatures, FN-DSA achieves the best transport feasibility due to its compact signature, while HQC is uniformly infeasible and SLH-DSA is nearly uniformly infeasible, quantifying the CAN-FD bandwidth premium of algorithmic diversity. System-side traffic shaping—staggered startup and reserved bus windows—outperforms algorithm substitution as a mitigation strategy. To the best of our knowledge, these findings constitute the first design-space map of PQC artifact transport on CAN-FD and provide actionable deployment guidelines for post-quantum transition. Full article
(This article belongs to the Special Issue Information Security: Threats and Attacks)
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22 pages, 2242 KB  
Article
Deterministic Boolean-Algebra Framework for Interpretable and Energy-Efficient Phishing URL Detection in Real Time
by Ludmila Babala, Khrystyna Lipianina-Honcharenko and Oleksandr Osolinskyi
Appl. Sci. 2026, 16(5), 2170; https://doi.org/10.3390/app16052170 - 24 Feb 2026
Viewed by 381
Abstract
Phishing attacks present a critical cybersecurity threat, with global financial losses exceeding USD 70 million in 2024. Modern machine-learning-based detection methods achieve high accuracy but have fundamental limitations, including lack of interpretability, significant computational requirements, and high energy consumption, which restrict their use [...] Read more.
Phishing attacks present a critical cybersecurity threat, with global financial losses exceeding USD 70 million in 2024. Modern machine-learning-based detection methods achieve high accuracy but have fundamental limitations, including lack of interpretability, significant computational requirements, and high energy consumption, which restrict their use in resource-constrained environments. This research presents a novel deterministic approach based on Boolean algebra for detecting phishing URLs. The method employs a 15-dimensional Boolean feature space covering structural, protocol, content-based, infrastructure, and reputation-based features, formalized as mathematically rigorous logical rules. Experimental evaluation which based on a balanced dataset of 50,000 URLs demonstrated a classification accuracy of 89.1% along with substantial operational advantages: processing latency of approximately 1 ms (24–69× faster), power consumption of 4.8 mW (108–250× lower), and full decision interpretability unlike machine learning methods. The proposed Boolean approach enables transparent, energy-efficient, and high-performance threat detection suitable for real-time cybersecurity applications, establishing a foundation for next-generation security systems with verifiable detection mechanisms. The proposed system is not intended to replace advanced ML-based detection systems; rather, it serves as an additional first line of defense, providing rapid initial filtering with minimal resource overhead and forwarding complex or borderline cases to ML systems for secondary verification. Full article
(This article belongs to the Special Issue Information Security: Threats and Attacks)
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36 pages, 2219 KB  
Article
Automated Malware Source Code Generation via Uncensored LLMs and Adversarial Evasion of Censored Model
by Raúl Acosta-Bermejo, José Alexis Terrazas-Chavez and Eleazar Aguirre-Anaya
Appl. Sci. 2025, 15(17), 9252; https://doi.org/10.3390/app15179252 - 22 Aug 2025
Cited by 3 | Viewed by 7958
Abstract
Malicious programs, commonly called malware, have had a pervasive presence in the world for nearly forty years and have continued to evolve and multiply exponentially. On the other hand, there are multiple research works focused on malware detection with different strategies that seem [...] Read more.
Malicious programs, commonly called malware, have had a pervasive presence in the world for nearly forty years and have continued to evolve and multiply exponentially. On the other hand, there are multiple research works focused on malware detection with different strategies that seem to work only temporarily, as new attack tactics and techniques quickly emerge. There are increasing proposals to analyze the problem from the attacker’s perspective, as suggested by MITRE ATT&CK. This article presents a proposal that utilizes Large Language Models (LLMs) to generate malware and understand its generation from the perspective of a red team. It demonstrates how to create malware using current models that incorporate censorship, and a specialized model is trained (fine-tuned) to generate code, enabling it to learn how to create malware. Both scenarios are evaluated using the pass@k metric and a controlled execution environment (malware lab) to prevent its spread. Full article
(This article belongs to the Special Issue Information Security: Threats and Attacks)
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