Symmetry/Asymmetry in Data Science and Information Security
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 1 June 2026 | Viewed by 51
Special Issue Editors
Interests: cybersecurity; machine learning; artificial intelligence
Special Issue Information
Dear Colleagues,
The fast-paced evolution of data-driven technologies has transformed the way we collect, analyze, and secure information. Data science and information security increasingly rely on detecting hidden patterns and structures, where the concepts of symmetry and asymmetry play a crucial role. Symmetry often provides balance, consistency, and predictability in data and algorithms, while asymmetry highlights irregularities, imbalances, and vulnerabilities that may signal novel insights or potential security threats.
This Special Issue explores how symmetry and asymmetry shape theoretical models, computational methods, and practical applications across data science and information security. We aim to bridge the gap between data science and cybersecurity, highlighting how symmetry and asymmetry can inform the development of robust, data-driven security strategies. We welcome both original research articles and reviews that explore theoretical advances, methodological innovations, and practical applications at the intersection of these fields. By bringing together contributions from mathematics, computer science, and engineering, this Special Issue seeks to promote interdisciplinary collaboration and novel approaches.
We welcome original research articles and reviews that advance the understanding and application of symmetry and asymmetry in this domain. Research areas may include (but are not limited to) the following:
- Symmetry and asymmetry in cryptographic protocols and information security frameworks;
- Data imbalance, distribution asymmetry, and their impacts on machine learning and AI;
- Anomaly and intrusion detection through symmetrical/asymmetrical modelling;
- Symmetry-based methods for data anonymisation, privacy, and risk analysis;
- Secure big data analytics and blockchain applications involving symmetry/asymmetry;
- Theoretical and applied studies on symmetry in data structures and algorithms.
We look forward to receiving your contributions.
Dr. Rejwan Bin Sulaiman
Dr. Rao Faizan Ali
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
- asymmetry
- data science
- information security
- cryptography
- machine learning
- anomaly detection
- data imbalance
- privacy-preserving computing
- blockchain security
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