Security and Privacy Challenges in Integrated IoT and Edge Systems

Dear Colleagues,

The convergence of the Internet of Things (IoT) and edge computing is transforming how data are processed, analyzed, and acted upon across diverse domains such as smart cities, healthcare, industrial automation, and autonomous systems. By bringing intelligence closer to the data source, IoT–edge integration enables ultra-low latency, real-time decision-making, and scalable applications. At the same time, this transformation introduces unprecedented security and privacy challenges.

IoT–edge systems are inherently decentralized, heterogeneous, and resource-constrained, which makes them particularly vulnerable to novel attack surfaces. Adversaries exploit weaknesses in communication protocols, device firmware, and distributed learning processes, while emerging issues such as generative AI-enabled cyberattacks, quantum-era vulnerabilities, and multi-modal edge intelligence further expand the landscape of risks. At the same time, ensuring resilience, sustainability, and trustworthy AI at the edge represents a next-generation research frontier.

This Special Issue aims to provide a forum for the latest advances in securing integrated IoT–edge ecosystems. We welcome contributions ranging from theoretical frameworks and algorithmic innovations to system architectures, prototypes, and real-world case studies. Our goal is to explore both foundational approaches and emerging technologies that will shape the next generation of secure, privacy-preserving IoT–edge systems.

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

• Lightweight cryptographic and authentication protocols for IoT–edge devices;
• Threat modeling, risk assessment, and vulnerability analysis in IoT–edge environments;
• Privacy-preserving machine learning and federated learning at the edge;
• Blockchain and distributed ledger technologies for IoT–edge security;
• Zero-trust frameworks and adaptive access control in decentralized IoT–edge systems;
• Intrusion detection and anomaly detection using edge AI;
• Adversarial attack detection, model poisoning, and defense in federated edge intelligence;
• Generative AI-enabled threats and AI-driven defenses for IoT–edge networks;
• Digital twin-based security validation and predictive intrusion modeling;
• Self-healing and autonomous recovery mechanisms for resilient IoT–edge infrastructures;
• Post-quantum cryptography and lightweight PQC algorithms for IoT–edge integration;
• Zero-knowledge proofs and advanced privacy-preserving protocols for real-time IoT data;
• Secure resource management, task offloading, and orchestration at the edge;
• Energy–security tradeoffs and sustainable security solutions in green IoT–edge systems;
• Security and privacy challenges in critical IoT–edge applications (healthcare, smart grid, transportation, Industry 4.0);
• Standardization and interoperability issues for multi-vendor IoT–edge platforms.

We invite original research articles and comprehensive reviews to this Special Issue. By showcasing cutting-edge approaches and forward-looking solutions, we aim to build a strong body of knowledge that advances the security and privacy of integrated IoT–edge ecosystems.

Dr. Mikail Mohammed Salim
Dr. Abir EL Azzaoui
Guest Editors

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• IoT security
• edge computing
• privacy-preserving AI
• federated learning
• blockchain
• zero-trust security
• generative AI threats
• digital twin security
• post-quantum cryptography
• cyber resilience