Security and Privacy in Distributed and Trustless Systems

Dear Colleagues,

Distributed and trustless systems are becoming a foundational paradigm for modern data-driven applications, enabling large-scale collaboration without relying on centralized authorities or fully trusted intermediaries. Such systems, including blockchain networks, federated learning frameworks, decentralized AI, and multi-agent platforms, introduce new opportunities for secure data sharing and autonomous coordination, while simultaneously raising critical challenges in data security and privacy protection.

This Topic aims to explore recent advances in security- and privacy-preserving techniques for distributed and trustless environments. We invite contributions that investigate theoretical foundations, algorithmic designs, system architectures, and practical deployments addressing threats such as data leakage, inference attacks, malicious participants, and trust misalignment. Topics of interest include, but are not limited to, cryptographic protocols, secure and verifiable computation, privacy-preserving machine learning, decentralized data governance, and trustworthy AI systems. By bringing together interdisciplinary research from security, distributed systems, and artificial intelligence, this Topic seeks to provide a comprehensive view of emerging challenges and solutions for building secure, privacy-aware, and trustworthy distributed systems.

Dr. Bruce Gu
Dr. Longxiang Gao
Topic Editors