Symmetries and Symmetry-Breaking in Data Security, 2nd Edition

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

Deadline for manuscript submissions: 18 August 2026 | Viewed by 875

Special Issue Editors


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Guest Editor
School of Geographical Sciences, Nanjing Normal University, Nanjing 210023, China
Interests: geographic information security theory, technology and application
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Information Engineering, Yangzhou University, Yangzhou 225127, China
Interests: data security; AI security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Data security is fundamental to protecting the integrity and reliability of information in our increasingly digital world, ensuring trust and safety for individuals, businesses, and governments alike. Symmetries and symmetry-breaking play significant roles in data security, and their study provides valuable insights and tools for developing more secure and resilient data protection methods. Recently, many researchers have concentrated on watermarking techniques for data protection, encryption methods to ensure data integrity and confidentiality, secure data transactions, and privacy-preserving computation strategies to enhance data security. Additionally, there is a focus on the dynamic interplay between attacks and defensive measures in data security, emphasizing innovative approaches to mitigate threats. Understanding the concepts of symmetries and symmetry-breaking allows security professionals to anticipate potential vulnerabilities and design methods that are robust against a wide range of threats.

This Special Issue invites contributions exploring the role of symmetries and their disruption in data security. It seeks to address both theoretical and practical aspects of how symmetry principles can enhance or compromise security mechanisms across various domains.

Prof. Dr. Na Ren
Dr. Weitong Chen
Guest Editors

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Keywords

  • data security
  • digital watermark
  • data encryption
  • data transactions
  • privacy-preserving computation
  • attack and defense

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Published Papers (1 paper)

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Research

19 pages, 1767 KB  
Article
GCMark: Robust Image Watermarking with Gated Feature Selection and Cover-Guided Expansion
by Lingjun Zou, Yuheng Li and Wei Liu
Symmetry 2026, 18(2), 241; https://doi.org/10.3390/sym18020241 - 29 Jan 2026
Viewed by 599
Abstract
Deep learning-based methods have achieved promising performance in image watermarking tasks due to their powerful capability to fully exploit the rich information present in images, which is crucial for ensuring watermark robustness. Although existing methods have improved robustness against various distortions, directly using [...] Read more.
Deep learning-based methods have achieved promising performance in image watermarking tasks due to their powerful capability to fully exploit the rich information present in images, which is crucial for ensuring watermark robustness. Although existing methods have improved robustness against various distortions, directly using deep neural networks for feature extraction and watermark expansion often introduces irrelevant and redundant features, thereby limiting the watermarking model’s imperceptibility and robustness. To address these limitations, in this paper, we introduce a robust image watermarking framework (GCMark) based on Gated Feature Selection and Cover-Guided Expansion, which consists of two key components: (1) the Dual-Stage Gated Modulation Block (DSGMB) that serves as the core backbone of both the encoder and decoder, adaptively suppressing irrelevant or redundant activations to enable more precise watermark embedding and extraction; (2) the Cover-Guided Message Expansion Block (CGMEB), which exploits the cover image’s structural features to guide watermark message expansion. By promoting a structurally consistent and well-balanced fusion between the watermark and host image, this implicit symmetry facilitates stable watermark propagation and enhances resilience against various distortions without introducing noticeable visual artifacts. Extensive experimental results demonstrate that the proposed GCMark framework outperforms existing methods with respect to both robustness and imperceptibility. Full article
(This article belongs to the Special Issue Symmetries and Symmetry-Breaking in Data Security, 2nd Edition)
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