applsci-logo

Journal Browser

Journal Browser

Approaches to Cyber Attacks and Malware Detection

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 June 2025 | Viewed by 536

Special Issue Editors


E-Mail Website
Guest Editor
Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City 04440, Mexico
Interests: data mining; cybersecurity; malware detection; threat modeling; threat intelligence; network traffic analysis

E-Mail Website
Guest Editor
Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City 04440, Mexico
Interests: data mining; video processing; motion detection; biometrics; deep learning; computer vision

E-Mail Website
Guest Editor
Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City 04440, Mexico
Interests: data mining; cybersecurity; malware detection; threat modeling; threat intelligence; network traffic analysis

Special Issue Information

Dear Colleagues,

The detection of cyberattacks and malware has been a pressing topic in recent years. Although techniques and procedures have been developed to mitigate various threats, attack vectors, exploitation surfaces, and malicious anomalies in different information systems, malicious actors have refined their methods to evade detection and eradication. Therefore, in this ongoing race between detection and response, it is crucial to refine the scope of analysis, modeling, mitigation, and remediation across the vast array of attacks and malware strains by proposing innovative and effective solutions. This Special Issue focuses on the study of algorithms, tactics, procedures, workflows, tools, and technologies that can combat cyberattacks and malware. Topics of interest include, but are not limited to, the following:

AI and ML for cyberattack and malware detection:

  • Zero-day exploitation, detection, and remediation;
  • Behavioral analysis for threat modeling for cyberattack and malware strains;
  • Threat hunting for cyberattack and malware;
  • Adversarial simulation for cyberattack and malware;
  • Blockchain-based solutions for cyberattack and malware prevention;
  • Automated incident response for cyberattack and malware;
  • Malware and cyberattack countermeasures in cloud and IoT environments;
  • Advanced persistent threat recognition, analysis, and mitigation.

Dr. Aldo Hernandez-Suarez
Dr. Jose Portillo-Portillo
Prof. Dr. Gabriel Sanchez-Perez
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

  • cybersecurity
  • malware detection
  • threat intelligence
  • network traffic analysis
  • behavioral analytics
  • advanced persistent threats
  • threat modeling
  • zero-day exploitation
  • automated incident response
  • cloud security

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

14 pages, 1019 KiB  
Article
Enhanced Blockchain-Based Data Poisoning Defense Mechanism
by Song-Kyoo Kim
Appl. Sci. 2025, 15(7), 4069; https://doi.org/10.3390/app15074069 - 7 Apr 2025
Viewed by 285
Abstract
This paper deals with a new secured execution environment which adapts blockchain technology to defend artificial intelligence (AI) models against data poisoning (DP) attacks. The Blockchain Governance Game (BGG) is a theoretical framework for analyzing the network to provide the decision-making moment for [...] Read more.
This paper deals with a new secured execution environment which adapts blockchain technology to defend artificial intelligence (AI) models against data poisoning (DP) attacks. The Blockchain Governance Game (BGG) is a theoretical framework for analyzing the network to provide the decision-making moment for taking preliminary cybersecurity actions before DP attacks. This innovative method for conventional decentralized network securities is adapted into a DP defense for AI models in this paper. The core components in the DP defense network, including the Predictor and the BGG engine, are fully implemented. This research concerns the first blockchain-based DP defense mechanism which establishes an innovative framework for DP defense based on the BGG. The simulation in the paper demonstrates realistic DP attack situations targeting AI models. This new controller is newly designed to provide sufficient cybersecurity performance measures even with minimal data collection and limited computing power. Additionally, this research will be helpful for those considering using blockchain to implement a DP defense mechanism. Full article
(This article belongs to the Special Issue Approaches to Cyber Attacks and Malware Detection)
Show Figures

Figure 1

Back to TopTop