Spear or Shield: Leveraging Generative AI to Tackle Security Threats of Intelligent Network Services

TL;DR

This paper explores how Generative AI can both pose security threats and serve as a defense in intelligent network services, analyzing attack-defense dynamics and demonstrating energy-efficient defense strategies.

Contribution

It provides a comprehensive overview of GAI applications in network security, highlights its dual roles, and presents a case study on energy-efficient defense mechanisms against data poisoning.

Findings

AI-optimized diffusion defense reduces energy by 8.7%

Defense decreases retransmissions from 32 to 6 images

GAI's dual role enhances security and efficiency

Abstract

Generative AI (GAI) models have been rapidly advancing, with a wide range of applications including intelligent networks and mobile AI-generated content (AIGC) services. Despite their numerous applications and potential, such models create opportunities for novel security challenges. In this paper, we examine the challenges and opportunities of GAI in the realm of the security of intelligent network AIGC services such as suggesting security policies, 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 GAI landscape, highlighting its applications and the techniques underpinning these advancements, especially large language and diffusion models. Then, we investigate the dynamic interplay between GAI's spear and shield roles, highlighting two primary categories of potential GAI-related attacks and their respective defense strategies within wireless networks. A case study illustrates the impact of GAI 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 GAI in enhancing network security.