Spear or Shield: The Role of Generative AI in Intelligent Network Services

Hongyang Du; Dusit Niyato; Jiawen Kang; Zehui Xiong; Kwok-Yan Lam; Yuguang Fang; Yonghui Li

doi:10.1109/MNET.2025.3594769

Spear or Shield: The Role of Generative AI in Intelligent Network Services

Hongyang Du
, Dusit Niyato
, Jiawen Kang^*
, Zehui Xiong
, Kwok-Yan Lam
, Yuguang Fang
, Yonghui Li

^*Corresponding author for this work

Department of Computer Science

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

1 Citation (Scopus)

20 Downloads (CityUHK Scholars)

Abstract

Generative AI (GenAI) models have been rapidly advancing, with a wide range of applications including intelligent networks and mobile AI-generated content (AIGC) services. However, GenAI create opportunities for novel security challenges due to its wide range of services applications and potential capabilities. In this paper, we examine the challenges and opportunities of GenAI in the realm of the security of intelligent network services, acting as both a “spear” for potential attacks and a “shield” as an integral part of various defense mechanisms. First, we present a comprehensive overview of the GenAI landscape, highlighting its applications and the techniques underpinning these advancements, especially large language and diffusion models. Then, we investigate the dynamic interplay between GenAI's spear and shield roles, highlighting two primary categories of potential GenAI-related attacks and their respective defense strategies within wireless networks. A case study illustrates the impact of GenAI defense strategies on energy consumption in an image request scenario under data poisoning attack. Our results show that by employing an AI-optimized diffusion defense mechanism, energy can be reduced by 8.7%, and retransmission count can be decreased from 32 images, without defense, to just 6 images, showcasing the effectiveness of GenAI in enhancing network security. © 2025 IEEE.

© 2025 IEEE. All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies. Personal use is permitted,but republication/redistribution requires IEEE permission.

Original language	English
Pages (from-to)	312-321
Number of pages	10
Journal	IEEE Network
Volume	40
Issue number	1
Online published	1 Aug 2025
DOIs	https://doi.org/10.1109/MNET.2025.3594769
Publication status	Published - Jan 2026

Funding

This research is supported in part by the National Natural Science Foundation of China (NSFC) under Grants No. U22A2054, in part by The Hong Kong Jockey Club Charities Trust under Contract 2023-0108, in part by the National Research Foundation, Singapore and Infocomm Media Development Authority under its Future Communications Research & Development Programme (FCP-NTU-RG-2022-010 and FCP-ASTAR-TG-2022-003), Singapore Ministry of Education (MOE) Tier 1 (RG87/22 and RG24/24), the NTU Centre for Computational Technologies in Finance (NTU-CCTF), and the RIE2025 Industry Alignment Fund - Industry Collaboration Projects (IAF-ICP) (Award I2301E0026), administered by A*STAR, as well as supported by Alibaba Group and NTU Singapore through Alibaba-NTU Global e-Sustainability CorpLab (ANGEL).

Research Keywords

AI safety
diffusion model
digital trust
Generative AI
large language mdoel
network security

Publisher's Copyright Statement

COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: © 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Du, H., Niyato, D., Kang, J., Xiong, Z., Lam, K.-Y., Fang, Y., & Li, Y. (2025). Spear or Shield: The Role of Generative AI in Intelligent Network Services. IEEE Network. Advance online publication. https://doi.org/10.1109/MNET.2025.3594769

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title = "Spear or Shield: The Role of Generative AI in Intelligent Network Services",

abstract = "Generative AI (GenAI) models have been rapidly advancing, with a wide range of applications including intelligent networks and mobile AI-generated content (AIGC) services. However, GenAI create opportunities for novel security challenges due to its wide range of services applications and potential capabilities. In this paper, we examine the challenges and opportunities of GenAI in the realm of the security of intelligent network services, acting as both a “spear” for potential attacks and a “shield” as an integral part of various defense mechanisms. First, we present a comprehensive overview of the GenAI landscape, highlighting its applications and the techniques underpinning these advancements, especially large language and diffusion models. Then, we investigate the dynamic interplay between GenAI's spear and shield roles, highlighting two primary categories of potential GenAI-related attacks and their respective defense strategies within wireless networks. A case study illustrates the impact of GenAI defense strategies on energy consumption in an image request scenario under data poisoning attack. Our results show that by employing an AI-optimized diffusion defense mechanism, energy can be reduced by 8.7\%, and retransmission count can be decreased from 32 images, without defense, to just 6 images, showcasing the effectiveness of GenAI in enhancing network security. {\textcopyright} 2025 IEEE. {\textcopyright} 2025 IEEE. All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies. Personal use is permitted,but republication/redistribution requires IEEE permission. ",

keywords = "AI safety, diffusion model, digital trust, Generative AI, large language mdoel, network security",

author = "Hongyang Du and Dusit Niyato and Jiawen Kang and Zehui Xiong and Kwok-Yan Lam and Yuguang Fang and Yonghui Li",

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T2 - The Role of Generative AI in Intelligent Network Services

AU - Du, Hongyang

AU - Niyato, Dusit

AU - Kang, Jiawen

AU - Xiong, Zehui

AU - Lam, Kwok-Yan

AU - Fang, Yuguang

AU - Li, Yonghui

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AB - Generative AI (GenAI) models have been rapidly advancing, with a wide range of applications including intelligent networks and mobile AI-generated content (AIGC) services. However, GenAI create opportunities for novel security challenges due to its wide range of services applications and potential capabilities. In this paper, we examine the challenges and opportunities of GenAI in the realm of the security of intelligent network services, acting as both a “spear” for potential attacks and a “shield” as an integral part of various defense mechanisms. First, we present a comprehensive overview of the GenAI landscape, highlighting its applications and the techniques underpinning these advancements, especially large language and diffusion models. Then, we investigate the dynamic interplay between GenAI's spear and shield roles, highlighting two primary categories of potential GenAI-related attacks and their respective defense strategies within wireless networks. A case study illustrates the impact of GenAI defense strategies on energy consumption in an image request scenario under data poisoning attack. Our results show that by employing an AI-optimized diffusion defense mechanism, energy can be reduced by 8.7%, and retransmission count can be decreased from 32 images, without defense, to just 6 images, showcasing the effectiveness of GenAI in enhancing network security. © 2025 IEEE. © 2025 IEEE. All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies. Personal use is permitted,but republication/redistribution requires IEEE permission.

KW - AI safety

KW - diffusion model

KW - digital trust

KW - Generative AI

KW - large language mdoel

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DO - 10.1109/MNET.2025.3594769

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JO - IEEE Network

JF - IEEE Network

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Spear or Shield: The Role of Generative AI in Intelligent Network Services

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Research Keywords

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