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Applications Based on Symmetry in Cryptography and Information Security

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

Deadline for manuscript submissions: 15 November 2025 | Viewed by 512

Special Issue Editor


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Guest Editor
School of Computer Science, Shaanxi Normal University, Xi’an 710062, China
Interests: cryptography; information security
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Special Issue Information

Dear Colleagues,

Cryptography and information security are crucial fields that have been gaining significant attention due to their importance in protecting sensitive data and ensuring secure communications. They involve the use of various techniques and algorithms to encrypt and decrypt information and safeguard it from unauthorized access and attacks. This field is essential for maintaining information confidentiality, integrity, and availability in various sectors, including finance, healthcare, and government. Furthermore, symmetry plays an important role in cryptography information security.

This Special Issue aims to bring together researchers and practitioners from diverse disciplines to share their latest findings and advancements in cryptography and information security. We are particularly interested in submissions that explore novel approaches and developments in this field, including but not limited to secure computation, cryptography theory and algorithms, cryptographic engineering and applications, and intelligent security and privacy computing. Potential areas of interest include the development of new encryption algorithms, techniques for secure data transmission, methods for detecting and preventing cyber attacks, and approaches to ensuring the privacy and security of personal data.

We welcome submissions on topics including, but not limited to, the following:

  • Cryptographic protocols and secure communication systems;
  • Digital signatures and authentication methods;
  • Leakage-resilient cryptographic algorithms and their implementations;
  • Public-key encryption techniques and their security properties;
  • Cryptographic primitives for data integrity and authentication;
  • Functional encryption for secure data processing and analysis;
  • Security and privacy in cloud computing and big data analytics.

All submissions will undergo a rigorous peer-review process to ensure their quality and originality. Accepted papers will be published and accessible to all readers.

Dr. Yanwei Zhou
Guest Editor

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

  • cryptographic protocols and secure communication systems
  • digital signatures and authentication methods
  • leakage-resilient cryptographic algorithms and their implementations
  • public-key encryption techniques and their security properties
  • cryptographic primitives for data integrity and authentication
  • functional encryption for secure data processing and analysis
  • security and privacy in cloud computing and big data analytics.

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Published Papers (1 paper)

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Research

44 pages, 852 KiB  
Article
An Intelligent Risk Assessment Methodology for the Full Lifecycle Security of Data
by Jinhui Liu, Tianyi Han, Jingjing Zhao, Dejun Mu, Huan Liu and Bo Tang
Symmetry 2025, 17(6), 820; https://doi.org/10.3390/sym17060820 - 24 May 2025
Viewed by 294
Abstract
With the development of Internet of Things and artificial intelligence, large amounts of data exist in our daily life. In view of the limitations in current data security risk assessment research, this paper puts forward an intelligent data security risk assessment method based [...] Read more.
With the development of Internet of Things and artificial intelligence, large amounts of data exist in our daily life. In view of the limitations in current data security risk assessment research, this paper puts forward an intelligent data security risk assessment method based on an attention mechanism that spans the entire data lifecycle. The initial step involves formulating a security-risk evaluation index that spans all phases of the data lifecycle. By constructing a symmetric mapping of subjective and objective weights using the Analytic Hierarchy Process (AHP) and the Entropy Weight Method (EWM), both expert judgment and objective data are comprehensively considered to scientifically determine the weights of various risk indicators, thereby enhancing the rationality and objectivity of the assessment framework. Next, the fuzzy comprehensive evaluation method is used to label the risk level of the data, providing an essential basis for subsequent model training. Finally, leveraging the structurally symmetric attention mechanism, we design and train a neural network model for data security risk assessment, enabling automatic capture of complex features and nonlinear correlations within the data for more precise and accurate risk evaluations. The proposed risk assessment approach embodies symmetry in both the determination of indicator weights and the design of the neural network architecture. Experimental results indicate that our proposed method achieves high assessment accuracy and stability, effectively adapts to data security risk environments, and offers a feasible intelligent decision aid tool for data security management. Full article
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