Ramesh Kumar, Joy Dutta, M. Vamsi, Uma Sankararao Varri · 5 authors
The integration of Artificial Intelligence (AI) into sixth-generation (6G) networks is a foundational requirement for achieving unprecedented performance, but it also introduces a sophisticated threat landscape that legacy security frameworks cannot address. This paper presents a comprehensive review of this dual role of AI, analyzing its potential to both compromise and safeguard future networks. Since AI has the ability to both protect and compromise security and privacy, its implementation with 6G technology may sometimes be a double-edged sword. The primary objective of this survey is to systematically analyze existing research that integrates AI techniques into 6G architectures, focusing on their implications for security and privacy. Among the concerns being investigated is the fundamental privacy and security risk associated with 6G technologies. Therefore, in order to incorporate and confirm this foundational research as a platform for future research, we have developed a review on the specifics of 6G security and privacy. The methodology involves reviewing recent academic and industrial studies related to AI-enabled 6G frameworks, threat models, and defense mechanisms, with an emphasis on how AI contributes to intrusion detection, authentication, and privacy preservation. This paper begins with a historical analysis of previous networking technologies and how they impacted contemporary 6G networking improvements. Therefore, this article discusses extensively the aspects that have rendered 6G technology relevant as well as the ongoing 6G-based projects. In addition, it identifies and critically evaluates key enabling technologies, including distributed ledger technology (DLT/blockchain), physical layer security (PLS), terahertz (THz) communication, quantum computing, visible light communication (VLC), and distributed AI/ML, that underpin secure 6G environments. The paper concludes by summarizing open challenges, future research opportunities, and potential pathways for building trustworthy AI-driven 6G systems.
Even though the wireless network of 5G has not been investigated exhaustively, the sixth generation (6G) echo systems’ visionaries are already being debated. Therefore, to solidify and consolidate privacy and security within 6G networks, this paper examines edge computing and its convergence with blockchain in 6G: security challenges. Moreover, the paper examines how security might affect the wireless systems of the 6G, potential obstacles characterizing various 6G technologies, alongside possible remedies. This paper unveils the 6G security vision alongside key indicators of performance with tentative landscape threat premised upon predicted sixth generation infrastructure. Furthermore, a discussion of the privacy and security challenges that might emerge from the existing sixth generation applications and demands is presented. Additionally, the paper sheds light into the research-level projects and standardization efforts. Specific attention is accorded to discussion on the security consideration with 6G enhancing technologies, including quantum computing, visible light communication (VLC), distributed ML/AI, physical layer security, and distributed ledger technology (DLT). Overall, this paper seeks to guide the subsequent investigation of sixth generation privacy and security in the early stage of envisioning to practicality.
Although the fifth generation wireless networks are yet to be fully investigated, the vision and key elements of the 6th generation (6G) ecosystem have already come into discussion. In order to contribute to these efforts and delineate the security and privacy aspects of 6G networks, we survey how security may impact the envisioned 6G wireless systems with the possible challenges and potential solutions. Especially, we discuss the security and privacy challenges that may emerge with the 6G requirements, novel network architecture, applications and enabling technologies including distributed ledger technologies, physical layer security, distributed artificial intelligence (AI)/ machine learning (ML), Visible Light Communication (VLC), THz bands, and quantum communication
Although the fifth generation (5G) wireless networks are yet to be fully investigated, the visionaries of the 6th generation (6G) echo systems have already come into the discussion. Therefore, in order to consolidate and solidify the security and privacy in 6G networks, we survey how security may impact the envisioned 6G wireless systems, possible challenges with different 6G technologies, and the potential solutions. We provide our vision on 6G security and security key performance indicators (KPIs) with the tentative threat landscape based on the foreseen 6G network architecture. Moreover, we discuss the security and privacy challenges that may encounter with the available 6G requirements and potential 6G applications. We also give the reader some insights into the standardization efforts and research-level projects relevant to 6G security. In particular, we discuss the security considerations with 6G enabling technologies such as distributed ledger technology (DLT), physical layer security, distributed AI/ML, visible light communication (VLC), THz, and quantum computing. All in all, this work intends to provide enlightening guidance for the subsequent research of 6G security and privacy at this initial phase of vision towards reality.
Pradip Kumar Sharma, Shailendra Rathore, Jong Hyuk Park
The winds of change are blowing toward the multibillion dollar global consumer electronics (CE) industry, which includes companies that are engaged in the manufacturing of smart devices to enable smartconnected vehicles, transportation, health-care systems, home automation, and smart industry in the smart-city network. The rapid increase in the number and diversity of smart devices connected to the Internet has given rise to concerns about scalability, efficiency, flexibility, and availability in the existing smart-city network. The imminent energy crisis, radiofrequency spectrum, and constraints on the lifetime of smart devices have also emerged as critical challenges. To address these challenges, this article presents DistArch-SCNet, the efficient, scalable, blockchain-based distributed smart-city network architecture enabled by the light-fidelity (Li-Fi) communication technique.
Martin Hoffmann, Michael Wittke, Jörg Hähner, Christian Müller-Schloer
We propose a decentralized, self-organizing system architecture for wireless networked smart cameras (SCs) with pan, tilt, and zoom abilities. Each SC communicates with its neighbors and independently calculates the optimal position for its field of view. Thereby, SCs autonomously organize themselves and spatially partition the area they observe. This is achieved by a decentralized algorithm that makes way for self-organization in SC systems. The system quickly adapts to new situations caused by joining and failing nodes. Simulations with hundreds of cameras show that scalability and reliability are achieved. We analyze the performance of different camera densities and show that optimal surveillance coverage is achieved in a short time (20 s) while maintaining low communication traffic using a simulated 350-node outdoor SC system.