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Open AccessJournal ArticleDOI

Security and Privacy for 6G: A Survey on Prospective Technologies and Challenges

TLDR
In this article, the authors provide 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.
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, artificial intelligence (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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Citations
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Journal ArticleDOI

Metaverse for Healthcare: A Survey on Potential Applications, Challenges and Future Directions

TL;DR: This article provides a comprehensive review of the Metaverse for healthcare, emphasizing on the state of the art, the enabling technologies for adopting the MetaVERSE, the potential applications and the related projects.
Journal ArticleDOI

Multifunctional graphene/carbon fiber aerogels toward compatible electromagnetic wave absorption and shielding in gigahertz and terahertz bands with optimized radar cross section

TL;DR: In this article , ultralight and mechanically durable graphene/carbon fiber composite aerogels (CGAs) are synthesized via solvothermal reaction and freeze-drying.
Journal ArticleDOI

Five Facets of 6G: Research Challenges and Opportunities

TL;DR: In this paper , the authors provide a critical appraisal of the literature of promising techniques ranging from the associated architectures, networking, and applications, as well as designs, and advocate a further evolutionary step toward multi-component Pareto optimization.
Journal ArticleDOI

Future outlook on 6G technology for renewable energy sources (RES)

TL;DR: In this paper , the authors provide a detailed insight into the full potential in 6G for the acceleration of renewable energy sources (RES) with the faster and stable data bandwidth, including P2P energy trade market, vehicular network, wireless energy transfer, energy management system, smart grid, self-healing, smart batteries and AI-based weather forecasting.
Posted Content

Towards 6G Internet of Things: Recent Advances, Use Cases, and Open Challenges

TL;DR: In this article, the authors present recent advances in the 6G wireless networks, including the evolution from 1G to 5G communications, the research trends for 6G, enabling technologies, and state-of-the-art 6G projects.
References
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Journal ArticleDOI

Deep Learning Aided Grant-Free NOMA Toward Reliable Low-Latency Access in Tactile Internet of Things

TL;DR: A variational optimization problem to improve the reliability of grant-free NOMA is formulated by parameterizing the intractable variational function with a specially designed deep neural network, which incorporates random user activation and symbol spreading.
Journal ArticleDOI

Deep Learning-Based DDoS-Attack Detection for Cyber–Physical System Over 5G Network

TL;DR: This article proposes a consolidated framework, by utilizing deep convolutional neural networks (CNNs) and real network data, to provide early detection for distributed denial-of-service (DDoS) attacks orchestrated by a botnet that controls malicious devices.
Proceedings ArticleDOI

Privacy Attacks to the 4G and 5G Cellular Paging Protocols Using Side Channel Information

TL;DR: It is shown that the fixed nature of paging occasions can be exploited by an adversary in the vicinity of a victim to associate the victim’s softidentity with its paging occasion, with only a modest cost, through an attack dubbed ToRPEDO, which can enable an adversary to verify a victim's coarse-grained location information, inject fabricated paging messages, and mount denial-of-service attacks.
Journal ArticleDOI

Learning-Aided Physical Layer Authentication as an Intelligent Process

TL;DR: In this paper, an adaptive physical layer authentication scheme based on machine-learning is proposed to improve the reliability and robustness of PLS authentication in time-varying communication channels.
Journal ArticleDOI

The AI-Based Cyber Threat Landscape: A Survey

TL;DR: This study aims to explore existing studies of AI-based cyber attacks and to map them onto a proposed framework, providing insight into new threats, and explains how to apply this framework to analyze AI-like attacks in a hypothetical scenario of a critical smart grid infrastructure.