Data-Driven Intelligent Discovering and Symmetry: Theory, Method, and Security
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 31 October 2025 | Viewed by 162
Special Issue Editors
Interests: cybersecurity; artificial intelligence; big data; tensor network
Special Issue Information
Dear Colleagues,
Symmetry plays a crucial role in data-driven intelligent discovery, and has led to significant results in big data and AI. Symmetry is the bridge that connects data and artificial intelligence, reducing the complexity of data, improving the efficiency of learning, discovering physical laws, and enhancing the ability of models to generalize. Data-driven intelligent discovery and symmetry is a multi-dimensional, interdisciplinary field that not only requires theoretical support but also methodological and security considerations in practical applications. With the development of technology, the applicative scope of the field will continue to expand. Although significant progress has been made, several challenges persist. These include data-driven intelligent discovery and symmetry theory, and issues related to methods and security. In order to address these problems, this Special Issue welcomes the submission of articles that address the following topics:
- The representation of data;
- Symmetry problems in intelligent discovery;
- The theory and application of intelligent discovery;
- Design of multi-space optimization strategies in intelligent discovery;
- Big data analysis and cross-domain collaboration in social computing;
- Graph-based intelligent discovery;
- Symmetry problem in large-scale graph neural networks (GNNs);
- Graph convolutional networks (GCNs) and graph attention networks (GATs);
- Security in intelligent discovery;
- Social AI techniques in smart cities, industrial automation, healthcare systems, transportation networks, and energy management;
- Intelligent discovery in large-scale cyber–physical–social networks.
Dr. Puming Wang
Dr. Bin Yuan
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
- big data
- artificial intelligence for security
- symmetry and asymmetry in cybersecurity
- differentially private data analysis
- network security, privacy and trust
- system symmetry and security
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