Privacy-Preserving Computation and Secure Data Sharing in Modern Networks

A special issue of Computers (ISSN 2073-431X). This special issue belongs to the section "ICT Infrastructures for Cybersecurity".

Deadline for manuscript submissions: 30 April 2027 | Viewed by 149

Editors

The Department of Software Systems and Cybersecurity, Faculty of IT, Monash University, Clayton, Australia
Interests: cryptography; applied cryptography; cloud security; IoT security; blockchain security
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Science, Edith Cowan University, Joondalup, Australia
Interests: cyber security; privacy; Internet of Things; machine learning; network forensics
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Special Issue Information

Dear Colleagues,

The rapid growth of data-driven applications across cloud, edge, and distributed network environments has intensified the need for robust privacy-preserving computation and secure data sharing mechanisms. Modern networks—spanning IoT ecosystems, federated systems, and multi-party platforms—require innovative solutions that enable collaborative data use without exposing sensitive information.

This Special Issue focuses on emerging theories, architectures, and practical implementations that safeguard data confidentiality, integrity, and usability throughout its lifecycle. The aim of this Special Issue is to advance the state of the art in secure and privacy-aware data processing, fostering trust in next-generation networked systems and enabling compliant, resilient, and ethical data sharing practices.

Topics include, but are not limited to, the following:

  • Cryptographic techniques such as secure multi-party computation, homomorphic encryption, and zero-knowledge proofs;
  • System-level approaches like federated learning and trusted execution environments;
  • Privacy risks in AI pipelines;
  • Data anonymization and de-identification methods;
  • Secure data exchange protocols in heterogeneous and resource-constrained networks.

Dr. Hui Cui
Dr. Michael N. Johnstone
Guest Editors

Manuscript Submission Information

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Keywords

  • privacy-preserving computation
  • secure data sharing
  • secure multi-party computation
  • homomorphic encryption
  • federated learning
  • differential privacy
  • trusted execution environments
  • data anonymization
  • network security
  • distributed systems

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Published Papers

This special issue is now open for submission.
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