The field of Internet of Things (IoT) and Cyber-Physical Systems (CPS) is moving towards enhanced security and reliability. Researchers are exploring innovative solutions to tackle the challenges of secure data transmission, smart contract execution, and cyber attack detection. The use of hybrid statistical-deep learning methods, lattice-based homomorphic ring signature schemes, and blockchain technology are being investigated to improve the security and transparency of IoT and CPS applications. Noteworthy papers include:
- Cyber Attacks Detection, Prevention, and Source Localization in Digital Substation Communication using Hybrid Statistical-Deep Learning, which proposes a novel method for detecting and preventing cyber attacks in digital substations.
- Stealtooth: Breaking Bluetooth Security Abusing Silent Automatic Pairing, which presents a new attack that abuses vulnerabilities in automatic pairing functions in commercial Bluetooth devices.
- Linearly Homomorphic Ring Signature Scheme over Lattices, which proposes the first lattice-based linearly homomorphic ring signature scheme, providing a post-quantum-secure solution for applications requiring anonymous data provenance and verifiable homomorphic computation.