Design and Implementation of a 5G Security Testbed for AI Solution Validation

The growing adoption of 5G private networks has significantly enhanced industries such as smart factories, autonomous vehicles, and smart homes, thanks to their high-speed data transmission, low latency, and support for large-scale device connectivity. These networks have driven advancements in real-time monitoring and process automation, boosting productivity and efficiency while reducing costs. However, the deployment of 5G private networks has also introduced various security challenges, particularly with the emergence of AI-driven technologies. This paper discusses these challenges, focusing on the design and implementation of a 5G security testbed to validate AI solutions within such environments. Key security threats associated with 5G private networks include the exploitation of AI and generative AI for sophisticated phishing and spoofing attacks, the hacking of autonomous vehicles and smart homes that can compromise both safety and privacy, and security breaches in AI-based smart factory systems, which could lead to operational disruptions and economic losses. These risks emphasize the need for proactive countermeasures to ensure the integrity and security of 5G private networks. This paper verifies the security of AI-based applications implemented through a testbed using Nokia's 5G network system and provides the necessary configurations for the stable deployment of AI-based service solutions.

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Publication Details

Published
2024-10-16
DOI
https://doi.org/10.1109/ictc62082.2024.10827562
Primary Topic
Smart Systems and Machine Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Design and Implementation of a 5G Security Testbed for AI Solution Validation

Jaeuk Kwon, Kyucheol Cho, Jihun Seo, Mahnsuk Yoon
Smart Systems and Machine Learning
article

Design and Implementation of a 5G Security Testbed for AI Solution Validation

Jaeuk Kwon, Kyucheol Cho, Jihun Seo, Mahnsuk Yoon
article en

Abstract

The growing adoption of 5G private networks has significantly enhanced industries such as smart factories, autonomous vehicles, and smart homes, thanks to their high-speed data transmission, low latency, and support for large-scale device connectivity. These networks have driven advancements in real-time monitoring and process automation, boosting productivity and efficiency while reducing costs. However, the deployment of 5G private networks has also introduced various security challenges, particularly with the emergence of AI-driven technologies. This paper discusses these challenges, focusing on the design and implementation of a 5G security testbed to validate AI solutions within such environments. Key security threats associated with 5G private networks include the exploitation of AI and generative AI for sophisticated phishing and spoofing attacks, the hacking of autonomous vehicles and smart homes that can compromise both safety and privacy, and security breaches in AI-based smart factory systems, which could lead to operational disruptions and economic losses. These risks emphasize the need for proactive countermeasures to ensure the integrity and security of 5G private networks. This paper verifies the security of AI-based applications implemented through a testbed using Nokia's 5G network system and provides the necessary configurations for the stable deployment of AI-based service solutions.

Korea Transport Institute (KR), Kyungpook National University (KR), Gumi Electronics & Information Technology Research Institute (South Korea) (KR)
Openalex Percentile: Top 70%
Smart Systems and Machine Learning
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