Special Issues

Keywords: IoT security; cybersecurity attacks; anomaly detection; intrusion detection; machine learning; AI-driven security; blockchain; edge computing; threat monitoring; data fusion; privacy-preserving techniques

(This special issue belongs to the Section Security Engineering & Applications)

Keywords: cybersecurity and privacy in industrial environments; security in cyber– physical environments; cryptography in I4.0; security and privacy in industrial control systems; IoT security and privacy; IoT system and network security; privacy protection and privacy-by-design; blockchains and smart contracts for IoT; trust issues in intelligent IoT devices; IoT threat detection and risk management; incident response and vulnerability management in IoT infrastructures; IoT privacy protection; secure data management and trading in industrial environments; privacy-enhancing technologies for Ι ο Τ devices; IoT Identity management; artificial intelligence (AI)-based security; machine learning and data protection for I4.0; standardization activities for I4.0 security; quantum and post-quantum I4.0 cryptography; IoT side-channel attacks

(This special issue belongs to the Section Privacy)

(This special issue belongs to the Section Privacy)

Keywords: cryptography and cryptanalysis; applied cryptography; cryptography for iot and blockchains; cryptography for secure computing; cryptography for data protection; privacy-preserving technologies

(This special issue belongs to the Section Cryptography and Cryptology)

Keywords: cryptography for smart grids; post-quantum cryptography for smart grids; AI for smart grid security; deep learning for smart grid security; distributed energy resource (DER) security; transformer security; large language models (LLMs) for smart grid security; intrusion detection and anomaly detection in smart grid networks; secure communication protocols for smart grids (SCADA; IEC 61850; DNP3; etc.); blockchain and distributed ledger technologies for smart grid security; zero-trust architectures for smart grid infrastructures; lightweight cryptography for constrained smart grid devices; hybrid classical– post-quantum cryptographic protocols in grid communications; hardware security modules (HSMs) and secure key management in smart grid environments; federated learning for smart grid security and privacy preservation; adversarial machine learning and robustness in smart grid AI models; reinforcement learning for attack detection and response in grid operations; graph neural networks (GNNs) for power grid anomaly detection; security of demand response management and advanced metering infrastructure (AMI); edge and fog computing security for distributed smart grid applications; cloud and data center security in smart grid ecosystems; cyber– physical attack detection; modeling; and mitigation in smart grid systems; quantum machine learning for smart grid intrusion detection and forecasting; digital twins and simulation frameworks for testing smart grid cyber resilience; privacy-preserving data analytics for energy consumption data; regulatory and compliance frameworks for smart grid cybersecurity; NIST/ISO/IEC standardization and adoption for smart grid systems; risk assessment; threat modeling; and incident response in smart grids; economic and societal impacts of cyber attacks on smart grids

(This special issue belongs to the Section Security Engineering & Applications)