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Security and privacy for 6G: A survey on prospective technologies and challenges (2108.11861v2)

Published 26 Aug 2021 in cs.CR and cs.NI

Abstract: Sixth-generation (6G) mobile networks will have to cope with diverse threats on a space-air-ground integrated network environment, novel technologies, and an accessible user information explosion. However, for now, security and privacy issues for 6G remain largely in concept. This survey provides a systematic overview of security and privacy issues based on prospective technologies for 6G in the physical, connection, and service layers, as well as through lessons learned from the failures of existing security architectures and state-of-the-art defenses. Two key lessons learned are as follows. First, other than inheriting vulnerabilities from the previous generations, 6G has new threat vectors from new radio technologies, such as the exposed location of radio stripes in ultra-massive MIMO systems at Terahertz bands and attacks against pervasive intelligence. Second, physical layer protection, deep network slicing, quantum-safe communications, AI security, platform-agnostic security, real-time adaptive security, and novel data protection mechanisms such as distributed ledgers and differential privacy are the top promising techniques to mitigate the attack magnitude and personal data breaches substantially.

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Authors (5)
  1. Van-Linh Nguyen (5 papers)
  2. Po-Ching Lin (3 papers)
  3. Bo-Chao Cheng (1 paper)
  4. Ren-Hung Hwang (6 papers)
  5. Ying-Dar Lin (7 papers)
Citations (241)

Summary

Security and Privacy in 6G Mobile Networks: Prospective Technologies and Challenges

The paper, "Security and Privacy for 6G: A Survey on Prospective Technologies and Challenges," provides a comprehensive analysis of the nascent issues within the security and privacy landscape for the anticipated sixth-generation (6G) mobile networks. As 6G networks evolve to accommodate a space-air-ground integrated environment and aim to deliver ultra-high speeds exceeding 1Tbps, the spectrum of security and privacy challenges adapts and expands correspondingly. This survey delineates both the inherited vulnerabilities from preceding generations and novel threats emerging from next-generation radio and intelligent systems.

Key Contributions and Results

The authors meticulously outline the vulnerabilities inherent in 6G systems, emphasizing novel threat vectors resultant from ultra-massive MIMO systems operating at Terahertz frequencies and pervasive intelligence advancements. The survey further identifies promising countermeasures such as physical layer protection, deep network slicing, quantum-safe communications, AI security, platform-agnostic security, and novel data protection mechanisms, including distributed ledgers and differential privacy. The elucidation of these techniques highlights their potential to significantly mitigate personal data breaches and attenuate attack magnitudes, showcasing the dual reliance on advancing both legacy and frontier technologies.

Implications and Theoretical Insights

The implications of advancing 6G network capabilities are vast, demanding a profound reconsideration of security architectures and privacy preservation mechanisms. The exploration of quantum-safe communications and AI's involvement in enhancing security architectures suggests a significant shift towards embedding security features at the core of network design, reflecting an architectural evolution rather than solely technological iteration. Furthermore, the adoption of distributed and decentralized models such as blockchain accentuates the push towards enhanced transparency and trust within 6G ecosystems.

The survey emphasizes the fluidity required in security approaches to accommodate heterogeneous network environments, pointing towards real-time adaptive security systems as a future necessity. Moreover, the potential reliance on AI as both a safeguard and a target within security frameworks suggests an inevitable intersection with ethical and regulatory domains, culminating in the need for robust AI-driven solutions while mitigating adversarial threats.

Practical Developments and Future Outlooks

Practically, the development of quantum-safe cryptographic methods poised to withstand emerging quantum threats exemplifies a pivotal area of focus. The potential for distributed ledger technologies to redefine trust and transparency in mobile networks is underscored, presenting opportunities for robust, verifiable interaction models. Similarly, distributed AI models, particularly federated learning, represent progressive strategies for managing and safeguarding data integrity across decentralized nodes.

Future research endeavors must concentrate on resolving the intricate balance between ensuring comprehensive security, maintaining high bandwidth, and upholding minimal latency standards. The anticipation of ethical AI utilization and the mitigation of its misuse foregrounds a critical dialogue necessary for guiding deployment strategies.

Conclusion

The survey paper articulates the sweeping changes and looming challenges confronting the evolution of 6G networks. By addressing both the legacy issues and contemporary advancements in security and privacy, the authors delineate a roadmap for researchers and industry stakeholders to navigate the complex landscape of next-generation mobile communications. As 6G unfolds, the synchronized progress in security and technical innovation will remain paramount to harnessing its full potential.