This paper provides a concise overview of how security must evolve as we move toward 6G smart networks, where communication, sensing, and computing become tightly integrated. It highlights that future systems will rely heavily on distributed AI/ML, making the protection of data, models, and learning pipelines a core requirement rather than an optional enhancement. The authors emphasize the need for trustworthy, explainable, and privacy-preserving AI to ensure that intelligence embedded throughout the network remains secure and reliable. A major focus of the work is the shift toward zero-touch, automated security, where continuous monitoring, threat analysis, and orchestration allow the network to react to risks dynamically. The paper also discusses the growing importance of time-sensitive and safety-critical services, noting that disruptions such as jamming or synchronization attacks can directly impact real-world operation in sectors like mobility and industrial automation.
In addition, the authors address the dual challenge of providing strong protection while keeping energy consumption under control. They point to multi-level security mechanisms, adaptive policies, and privacy-enhancing techniques as enablers for more sustainable operation. Finally, the paper stresses the urgency of adopting quantum-safe cryptographic solutions, as future networks must remain secure even in the presence of quantum-capable adversaries. Overall, the paper outlines a multi-dimensional roadmap for securing 6G—combining AI robustness, automation, real-time resilience, energy efficiency, and post-quantum security into a unified vision for next-generation networks.