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Symmetry
Special Issues
Studies of Symmetry and Asymmetry in Cryptography
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Studies of Symmetry and Asymmetry in Cryptography

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 633

Special Issue Editors

Prof. Dr. Zhijiang Li

E-Mail Website
Guest Editor
School of Information Management, Wuhan University, Wuhan, China
Interests: spatio-temporal big data; large model security; multi-modal trustworthy reasoning
Prof. Dr. Shengli Deng

E-Mail Website
Guest Editor
School of Information Management, Wuhan University, Wuhan, China
Interests: big data; user behaviour; information interaction
Dr. Rui Zhang

E-Mail Website
Guest Editor
School of Information Management, Wuhan University, Wuhan, China
Interests: artificial intelligence; multimodal learning; graph mining

Special Issue Information

Dear Colleagues,

Information security and confidentiality are critical in the digital age, with increasing challenges posed by data breaches, cyberattacks, and unauthorized access. This Special Issue aims to explore the theoretical and practical advances in secure communication, encryption, privacy-preserving technologies, and trusted computing. Emphasis is placed on how concepts of symmetry and asymmetry—particularly in cryptographic protocols, secure key exchange, and information hiding—can enhance security frameworks. Contributions discussing symmetric/asymmetric encryption, biometric security, quantum-safe systems, and security in AI applications are welcome. We encourage both theoretical and application-driven research that aligns with the broader theme of symmetry in information protection.

Prof. Dr. Zhijiang Li
Prof. Dr. Shengli Deng
Dr. Rui Zhang
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. 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

  • symmetric encryption
  • asymmetric encryption
  • confidentiality
  • secure communication
  • cryptographic protocols
  • privacy-preserving technologies
  • trusted computing
  • information hiding
  • cybersecurity
  • quantum-safe cryptography

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Published Papers (1 paper)

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Research

27 pages, 3074 KB  
Article
A New Asymmetric Track Filtering Algorithm Based on TCN-ResGRU-MHA
by Hanbao Wu, Yonggang Yang, Wei Chen and Yizhi Wang
Symmetry 2025, 17(12), 2094; https://doi.org/10.3390/sym17122094 - 5 Dec 2025
Viewed by 384
Abstract
Modern target tracking systems rely on radar as a sensor to detect targets and generate raw track points. These raw track points are affected by the radar’s own noise and the asymmetric non-Gaussian noise resulting from the nonlinear transformation from polar coordinates to [...] Read more.
Modern target tracking systems rely on radar as a sensor to detect targets and generate raw track points. These raw track points are affected by the radar’s own noise and the asymmetric non-Gaussian noise resulting from the nonlinear transformation from polar coordinates to Cartesian coordinates. Without effective processing, such data cannot directly support highly reliable situational awareness, early warning decisions, or weapon guidance. Track filtering, as a core component of target tracking, plays an irreplaceable foundational role in achieving real-time, accurate, and stable estimation of moving target states. Traditional deep learning filtering algorithms struggle with capturing long-term dependencies in high-dimensional spaces, often exhibiting high computational complexity, slow response to transient signals, and compromised noise suppression due to their inherent architectural asymmetries. In order to address these issues and balance the model’s high accuracy, strong real-time performance, and robustness, a new trajectory filtering algorithm based on a temporal convolutional network (TCN), Residual Gated Recurrent Unit (ResGRU), and multi-head attention (MHA) is proposed. The TCN-ResGRU-MHA hybrid structure we propose combines the parallel processing advantages and detail-capturing ability of a TCN with the residual learning capability of a ResGRU, and introduces the MHA mechanism to achieve adaptive weighting of high-dimensional features. Using the root mean square error (RMSE) and Euclidean distance to evaluate the model effect, the experimental results show that the RMSE of TCN-ResGRU-MHA is 27.4621 (m) lower than CNN-GRU, which is an improvement of 15.99% in the complex scene of high latitude, and the distance is 37.906 (m) lower than CNN-GRU, which is an improvement of 18.65%. These results demonstrate its effectiveness in filtering and tracking tasks in high-latitude complex scenarios. Full article
(This article belongs to the Special Issue Studies of Symmetry and Asymmetry in Cryptography)
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