Data Mining and Machine Learning in Cybersecurity, 2nd Edition
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 10 October 2026 | Viewed by 1408
Special Issue Editors
Interests: artificial intelligence security; cyber attack and defense; situation awareness analysis; big data analysis; intelligent connected vehicle; knowledge graph
Special Issues, Collections and Topics in MDPI journals
Interests: graph processing; graph neural networks; spatial data processing
Special Issues, Collections and Topics in MDPI journals
Interests: big data; data mining; spatial databases; cyberspace security
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue aims to showcase the latest advancements in the field of data mining and machine learning in cybersecurity. The information revolution has changed how we communicate all around the world and has drawn unprecedented attention to network security issues. This Special Issue seeks to explore innovative techniques, methodologies, and tools that enhance our ability to detect, analyze, and respond to network security effectively.
Authors are invited to contribute original research papers and conceptual articles addressing various aspects of network attack detection and situation awareness analysis for the comprehensive evaluation of various elements in the time and space environments of overall network security. This may include topics such as intrusion detection systems, anomaly detection algorithms, data mining/machine learning-driven approaches, threat intelligence integration, and real-time monitoring solutions.
In this Special Issue, we invite submissions exploring cutting-edge research and recent advances in the field of network security. Both theoretical and experimental studies are welcome, as are comprehensive review and survey papers.
Suitable topics include, but are not limited to, the following:
- Network attack detection;
- Situation awareness analysis;
- Anomaly detection;
- Intrusion detection systems;
- Cyber threat analysis;
- Network forensics;
- In-vehicle network security;
- Graph-based approaches for network security;
- Cyber adversarial attacks and defenses;
- Explainable artificial intelligence for network security.
Prof. Dr. Zhaoquan Gu
Dr. Xiaoyang Wang
Prof. Dr. Aiping Li
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
- network attack
- network defense
- artificial intelligence
- data mining
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Related Special Issue
- Data Mining and Machine Learning in Cybersecurity in Applied Sciences (4 articles)
