Applications Based on Symmetry in Adversarial Machine Learning
A special issue of Symmetry (ISSN 2073-8994).
Deadline for manuscript submissions: 31 January 2026 | Viewed by 27
Special Issue Editors
Interests: cybersecurity and privacy; machine learning; data management and data science
Interests: trustworthy machine learning; data stream mining; real-time prediction
Special Issue Information
Dear Colleagues,
Symmetry is a fundamental concept in adversarial machine learning that offers new opportunities to improve the robustness, security, and interpretability of modern learning systems. By harnessing symmetrical properties in data and model architectures, researchers can develop more effective defenses, identify vulnerabilities, and enhance the overall reliability of deep neural networks, large language models, and foundation models. As machine learning technologies increasingly permeate safety-critical applications, exploring symmetry in adversarial contexts is crucial for ensuring trustworthy and dependable AI systems.
This Special Issue, “Applications Based on Symmetry in Adversarial Machine Learning”, aims to bring together researchers and practitioners from diverse backgrounds to share their latest findings, methodologies, and advancements in this evolving field. We are particularly interested in studies that explore the interplay between symmetry and adversarial learning in areas such as computer vision, natural language processing, network security, autonomous systems, and large language models. We are soliciting contributions covering all related topics, including but not limited to cybersecurity, the Internet of Things, multimedia, networks, biometrics, behavior analysis, software engineering, digital health, simulation, and interdisciplinary applications. Both theoretical and application-oriented research articles are welcome.
We look forward to receiving your contributions.
Dr. Wanlun Ma
Dr. Yiliao Song
Dr. Xiao Chen
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. Symmetry is an international peer-reviewed open access monthly 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
- symmetry theories and applications
- adversarial machine learning
- adversarial attacks and defense
- artificial intelligence
- security, privacy and fairness
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