The field of cyber-physical system (CPS) security is rapidly evolving, with a focus on developing innovative solutions to protect against increasingly sophisticated attacks. A key direction in the field is the development of adaptable anomaly detection models that can detect attacks without requiring previously labeled data. Notably, there is a growing emphasis on cross-domain adaptation, sensor out-of-band vulnerabilities, and data-driven sensor selection to enhance the security and resilience of CPS. Recent research has also highlighted the importance of systematization frameworks to provide a comprehensive understanding of sensor hardware vulnerabilities and to guide the development of more secure sensors and CPS. The cybersecurity assessment of humanoid ecosystems is another important area of research, which involves evaluating the security profile of humanoid robots and developing quantitative methods to assess their security maturity levels. In related fields, the advent of quantum computing poses a substantial threat to traditional cryptographic systems, and researchers are actively exploring post-quantum cryptography (PQC) solutions to ensure a secure transition to a quantum-resistant cryptographic landscape. The integration of PQC algorithms into blockchain technology is a key area of focus, as blockchain's reliance on cryptographic protocols makes it vulnerable to quantum attacks. Additionally, the field of secure and private computation is rapidly advancing, with a focus on developing innovative solutions to protect sensitive data and ensure the integrity of complex systems. The development of efficient and scalable protocols for secure multi-party computation, homomorphic encryption, and zero-knowledge proofs has far-reaching implications for various industries, including finance, healthcare, and transportation. Furthermore, the field of artificial intelligence is moving towards a greater emphasis on governance and safety, with a focus on developing frameworks and mechanisms that can ensure the reliable and secure operation of AI systems. The field of AI security and risk assessment is also rapidly evolving, with a growing focus on addressing the unique challenges posed by adversarial machine learning threats and cognitive cybersecurity vulnerabilities. Overall, the fields of CPS security, cryptography, secure computation, and AI are rapidly advancing, with a growing emphasis on developing innovative solutions to protect against increasingly sophisticated attacks and ensure the security and integrity of complex systems.