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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 February 2026 | Viewed by 1620

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 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. 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 (1 paper)

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Research

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
Viewed by 1211
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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