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Special Issue on Emerging Encryption Techniques for Big Data Security

Despite their promise in revolutionizing data security for big data, emerging encryption techniques still face significant challenges. Many methods, such as fully homomorphic encryption, are computationally intensive and introduce considerable performance overhead, making them impractical for real-time applications. On the other hand, some encryption systems that are more suitable for deployment in big data environments face security challenges, such as searchable encryption schemes, which carry the risk of information leakage. Therefore, further research into emerging encryption technologies for big data is critical. Topics The aim of the proposed special issue is to promote research and reflect the most recent advances in emerging encryption techniques for big data, with emphasis on the following aspects, but certainly not limited to: - (Fully) Homomorphic Encryption; - Functional Encryption; - Identity-Based Encryption; - Attribute-Based Encryption; - Predicate Encryption; - Matching Encryption; - Broadcast Encryption; - Proxy Re-Encryption; - Searchable Encryption; - Message-Locked Encryption; - Order-Preserving Encryption; - Lightweight Encryption; - Honey Encryption; - Witness Encryption; - Deniable Encryption; - Anamorphic Encryption; - Kleptography. Open for Submission from 2025-04-01 Submission Deadline 2026-01-01

Participating journal

Submit your manuscript to this collection through the participating journal.

Editors

  • Ding Wang

    Nankai University, China wangding@nankai.edu.cn
  • Xiaofeng Chen

    Xidian University, China xfchen@xidian.edu.cn
  • Elisa Bertino

    Purdue University, USA bertino@purdue.edu

Articles

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