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Information Theory and Entropy Methods in Security Information Processing and Its Applications

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: 15 August 2026 | Viewed by 1331

Special Issue Editor


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Special Issue Information

Dear Colleagues,

Recent advancements in information theory and entropy methods have significantly enhanced modern approaches to information security and data privacy. These techniques provide robust frameworks for cryptography, anomaly detection, and secure communication, ensuring resilience against evolving cyber threats. This Special Issue seeks high-quality research exploring theoretical and applied aspects of entropy-driven security solutions, including stochastic processes in security, quantum information processing, and machine learning in security for next-generation protection mechanisms.

The scope of this Special Issue includes, but is not limited to, biometric systems leveraging entropy metrics, network security optimization through information-theoretic models, and cybersecurity strategies grounded in probabilistic and statistical methods. We welcome contributions addressing novel entropy-based measures for threat identification, privacy-preserving data analysis, and the intersection of AI with information-theoretic security. Both theoretical studies and practical applications demonstrating real-world impact are encouraged.

Researchers are invited to submit original articles, reviews, or case studies that advance the understanding of entropy-centric security paradigms. By fostering interdisciplinary dialogue, this Special Issue aims to bridge gaps between foundational information theory and cutting-edge security challenges, promoting innovative solutions for a safer digital landscape.

Prof. Dr. Carlos M. Travieso-González
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 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. Entropy 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 2600 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

  • information theory
  • entropy methods
  • information security and data privacy
  • anomaly detection
  • biometric systems
  • cryptography
  • network security
  • machine learning in security
  • quantum information processing
  • cybersecurity
  • stochastic processes in security
  • secure communication

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Published Papers (2 papers)

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Research

19 pages, 2726 KB  
Article
Power Distribution Internet of Things Security Risk Evaluation Based on Combined Weighting and Cloud Model
by Li Peng, Jiahai Tu, Siyuan Cai and Deng Chen
Entropy 2026, 28(4), 433; https://doi.org/10.3390/e28040433 - 12 Apr 2026
Viewed by 280
Abstract
With the interconnection and intercommunication of Internet of Things (IoT) devices, the security risks of Power Distribution Internet of Things (PDIoT) systems have increased accordingly. How to monitor and assess these risks has become a key issue for advancing the construction and implementation [...] Read more.
With the interconnection and intercommunication of Internet of Things (IoT) devices, the security risks of Power Distribution Internet of Things (PDIoT) systems have increased accordingly. How to monitor and assess these risks has become a key issue for advancing the construction and implementation of PDIoT. The traditional security evaluation methods mostly adopt a single weighting method and membership function, which are highly susceptible to subjective factors and have the characteristics of fuzziness and uncertainty. To address the problems, this paper proposes a security risk evaluation method of the PDIoT based on a combined weighting and cloud model. We first analyze the factors of security risks in PDIoT systems. A security evaluation index system for PDIoT was established based on factors from three aspects: the perception layer, network layer, and application layer, including 3 first-level indicators and 16 second-level indicators. Then, the analytic hierarchy process (AHP) and entropy weight method (EWM) are adopted for combined weighting to optimize the weight of each index; the cloud model is employed to calculate the standard evaluation and the comprehensive evaluation cloud. Subsequently, validity verification and cloud similarity calculation are performed to get the security state of the PDIoT. Finally the security evaluation level of the PDIoT system is obtained. An empirical test was conducted by taking the PDIoT of Meizhou Power Supply Bureau of Guangdong Power Grid as an example. The experimental results show that our method has better result distinguishability than the other three classical methods, allowing risk levels to be identified more clearly and intuitively. Full article
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22 pages, 311 KB  
Article
Accelerated Multisecret Sharing Scheme Using Fast Matrix Spectral Factorization
by Selda Çalkavur, Patrick Solé and Lasha Ephremidze
Entropy 2026, 28(4), 369; https://doi.org/10.3390/e28040369 - 25 Mar 2026
Viewed by 533
Abstract
In this paper, we propose a novel multisecret sharing (MSS) scheme that integrates a recently developed exponential-speedup matrix spectral factorization algorithm into the construction of paraunitary matrices over finite fields. By exploiting the block-matrix generalization of the Janashia-Lagvilava method, we significantly enhance the [...] Read more.
In this paper, we propose a novel multisecret sharing (MSS) scheme that integrates a recently developed exponential-speedup matrix spectral factorization algorithm into the construction of paraunitary matrices over finite fields. By exploiting the block-matrix generalization of the Janashia-Lagvilava method, we significantly enhance the efficiency and scalability of the MSS scheme. The proposed method ensures perfect secrecy, collusion resistance, and efficient reconstruction, while enabling practical deployment in large-scale distributed systems such as secure cloud storage, IoT networks, and blockchain authentication. Security and performance analyses demonstrate the superiority of the new approach over existing MSS schemes. Full article
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