Guest Editors
Prof. Hu Xiong
Email: xionghu.uestc@gmail.com
Affiliation: School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China
Homepage:
Research Interests: privacy-preserving blockchain-enabled federated learning, secure authentication protocols, encrypted data sharing, and transportation and IoT security
Dr. Abubaker Wahaballa
Email: wahaballah@arabeast.edu.sa
Affiliation: Computer Science Department, Arab East Colleges, Riyadh, Saudi Arabia
Research Interests: cryptography, blockchain security, deFi, privacy-preserving protocols, AI security, IoT and network security
Summary
The convergence of Artificial Intelligence (AI) and blockchain technology has created a paradigm shift in digital trust, with AI providing the cognitive power to detect complex threats and blockchain ensuring the integrity and decentralization of data. As these technologies become more intertwined, securing the AI–blockchain pipeline is critical to preventing sophisticated adversarial attacks and ensuring the resilience of future autonomous infrastructures.
This Special Issue aims to explore the synergistic relationship between AI and Blockchain, specifically focusing on how AI can enhance decentralized security and how Blockchain can safeguard AI lifecycles. We seek to gather cutting-edge research addressing the "double-edged" nature of these technologies – using AI to defend against automated exploits and leveraging blockchain to create verifiable, tamper-proof AI models. The scope includes theoretical frameworks, practical implementations, and privacy-preserving protocols designed to build a transparent, secure, and autonomous digital ecosystem.
Therefore, this Special Issue focuses on advancing the foundations, methodologies, and applications that ensure the security, trustworthiness, and resilience of AI-driven systems integrated with blockchain technologies.
The following subtopics are of particular interest to this Special Issue, including but not limited to:
· AI-powered threat detection and security analytics for blockchain networks and decentralized applications
· Secure and trustworthy AI lifecycle management using distributed ledger technologies
· Privacy-preserving machine learning (e.g., federated learning) supported by blockchain
· Verification, auditability, and integrity protection of AI models on-chain
· Adversarial attack mitigation and resilience in AI–blockchain environments
· Smart contract security enhanced through AI-based analysis and formal verification
· Cryptographic approaches such as Zero-Knowledge Proofs, MPC, and homomorphic encryption for secure AI computation
· Trust, governance, and accountability mechanisms for autonomous and decentralized AI systems
· Secure applications in FinTech, IoT, and cyber-physical infrastructures leveraging AI and blockchain integration
Keywords
artificial intelligence security; AI-powered cybersecurity; secure AI; blockchain security; trustworthy AI; privacy-preserving machine learning; federated learning; smart contract security; decentralized systems;
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