Special Issue on Secure Computation and In-depth Utilization over Encrypted Data

Raid advances in big data, artificial intelligence, and smart services are transforming how data are used. Data are no longer simply stored and managed; they are continually queried, analyzed and processed for applications such as model training and inference. As a result, the central challenge in data security has expanded from protecting data at rest and in transit to enabling meaningful computation while safeguarding the underlying information—sometimes described as making data “usable but invisible”.

Conventional cryptographic frameworks provide well-established methods for securing stored and transmitted data. However, their reliance on a “decrypt-then-compute” model is increasingly unsuitable for data-intensive applications because it requires information to be exposed before it can be processed. Enabling useful computation directly on protected data therefore requires advances in computational architectures, algorithm design and the theoretical foundations of cryptographic protocols. This need has driven the development of secure computation technologies that support data processing while limiting the disclosure of sensitive information.

Although secure computation has evolved into a relatively complete technical ecosystem, numerous fundamental theoretical and practical bottlenecks persist for in‑depth data utilization scenarios. For example, while secure multi‑party computation (SMPC) and fully homomorphic encryption (FHE) theoretically support collaborative computation and arbitrary operations on ciphertexts, their practical deployments face critical open challenges including communication overhead, computational latency, and efficient execution of complex non‑linear functions required by modern artificial intelligence.

More broadly, More broadly, encrypted-data processing involves inherent trade-offs among privacy guarantees, computational efficiency and analytical accuracy. Developing scalable cryptographic protocols for continual model training and inference—particularly secure computation for large language models (LLMs)—remains an important research frontier. These unresolved questions warrant a dedicated Special Issue examining emerging approaches to encrypted-data processing, from their theoretical foundations to their practical applications.

Topics

The Special Issue aims to showcase recent research and advances in secure computation and deep utilization technologies for encrypted data, with particular emphasis on, but not limited to, the following areas:

• Deep Utilization & Privacy-Preserving AI

• Secure Training and Continuous Inference over Encrypted Data
• Privacy-Preserving Machine Learning & Deep Learning
• Federated Learning and Decentralized AI Systems
• Secure Computation for Large Language Models

• Cryptographic Foundations for Secure Computation

• Fully Homomorphic Encryption & Partially Homomorphic Encryption
• Scalable Secure Multi-Party Computation
• Functional Encryption & Searchable Encryption
• Oblivious RAM (ORAM) & Private Information Retrieval

• Encrypted Data Query & Analysis Systems

• Scalable Systems for Encrypted Database Queries
• Secure Data Analytics and Mining over Ciphertexts
• Verifiable Computation for Big Data Processing

• Hardware Acceleration & System Architectures

• Cryptography for Machine Learning & Artificial Intelligence
• Hardware Acceleration for FHE/MPC
• Trusted Execution Environments (TEE) and Confidential Computing
• Hybrid Secure Computation Frameworks for Smart Services

• Adversarial Models & Advanced Threat Mitigation

• Security under Malicious Adversary Models in Deep Utilization
• Defenses against Data Poisoning and Model Inversion Attacks
• Side-Channel Analysis in Secure Computation Systems

Paper Solicitation

This issue is an open special issue inviting submissions from all researchers. The paper submissions are invited in two ways: conference and open call-for-papers.

• The 4th International Conference on Data Security and Privacy Protection (DSPP 2026)

The conference endeavors to facilitate the intellectual discussion and academic exchange focusing on the latest theories and practical applications in the emerging topics of the data security and privacy protection. DSPP 2026 intends to encourage the integration of diverse perspectives, the cross-fertilization of ideas, and serve as a platform for researchers, professionals, and students worldwide to share insights and disseminate their research findings. The organization committee of DSPP 2026 has been diligently preparing for the conference for more than 6 months. The conference now boasts a distinguished TPC comprising members from 20+ countries, alongside several world-famous scholars delivering keynote talks, which attracts a substantial number of high-quality papers. This year, we aim to increase the number of submissions to a level of 100+, with the goal of making it a more successful and sustainable conference.

The conference website is https://dspp2026.xidian.edu.cn/.

We plan to select the highest-quality papers from the accepted submissions based on the reviews (including comments and scores regarding originality and correctness) and the presentations during the conferences. Each selected paper must be substantially extended, with at least 50% difference from its conference version.

• Open Call-For-Papers

We plan to issue an open call-for-paper (CFP) by posting it on the major academic mailing list and websites, as well as sending it to active researchers interested in this domain globally. We anticipate a significant number of submissions through the open call for papers, after which we plan to select a limited number of papers from the submissions.

Each paper (including the selected papers from the conference) will undergo through a rigorous and conscientious peer-review process conducted by at least three international researchers. In total, we plan to include 8-12 papers in this special issue. The acceptance rate will be relatively low, as we prioritize the quality above all else. The anticipated readers of this special issue include both academic and industrial researchers working in relevant areas of data security and privacy protection.

Submission guidelines

All papers must be prepared in accordance with the Journal guidelines: https://www.keaipublishing.com/en/journals/cyber-security-and-applications/guide-for-authors/

Submitted papers should present original, unpublished work, relevant to one of the topics of the Special Issue.  All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation, by at least two independent reviewers. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process.

When submitting your manuscript online via the Editorial Manager system (https://www.editorialmanager.com/csa/default.aspx), please select "VSI: SCUED-DSPP2026" from the "Article Type" dropdown menu during the submission process.

Important Dates

• Submission Due: December 1, 2026
• Editorial Acceptance Deadline: 31 December 2027
• Final Notification: May 1, 2027
• Publication: 2027/2028

Guest Editors

Assoc. Prof. Guohua Tian

Xidian University, China

Email: ghtian@xidian.edu.cn

Assoc. Prof. Guohua Tian received the Ph.D. degree from Xidian University in 2023. Currently, he is an Associate Professor at the School of Cyber Engineering, Xidian University, and his main research interests include data security, blockchain security, and decentralized storage. He has published more than 30 research papers in referred international conferences and journals, such as USENIX Security, IEEE TDSC, IEEE TC, IEEE TMC, etc.

Prof. Chao Lin

Nanjing University of Aeronautics and Astronautics, China

Email: chaolin@nuaa.edu.cn

Prof. Chao Lin received his Ph.D. from the School of Cyber Science and Engineering at Wuhan University.He is currently a Research Professor with the College of Computer Science and Technology at Nanjing University of Aeronautics and Astronautics, China. His research interests mainly include Public-Key Cryptography, Blockchain, Payment Channels, and AI Security and Privacy. He has authored or co-authored more than 60 papers in leading conferences and journals, including CRYPTO, USENIX Security, ICML, IEEE ICDCS, IEEE TDSC, IEEE TIFS, and IEEE TSC. In addition to his research, he actively contributes to the academic community. He serves as an associate editor for journals such as IEEE TDSC, a Youth Editor for journals such as Research and Journal of Cyber Security, and has served on the program committees of conferences including USENIX Security 2027, Inscrypt 2025-2026, and IEEE ICPADS 2022.

Dr. Jun Shen

Shanghai University, China

Email: demon_sj@126.com

Dr. Jun Shen received the B.S. and M.S. from Nanjing University of Information Science and Technology, China in 2015 and 2018, respectively. She got the Ph.D. degree in Cyberspace Security from Xidian University in 2023. She is currently a lecturer with Shanghai University, China. Her research interests include data security, cloud computing and blockchains. She has published over 20 research papers in refereed international conferences and journals. Her work has been cited more than 1300 times at Google Scholar. She has been the principal investigator of a NSFC Youth Project, a Shanghai Science and Technology Innovation Action Plan “Sailing Program” Project, etc. She serves as a peer reviewer for IEEE Transactions on Dependable and Secure Computing, IEEE Transactions on Mobile Computing, etc.