Guarding 6G use cases: a deep dive into AI/ML threats in All-Senses meeting

IF 1.8 4区 计算机科学 Q3 TELECOMMUNICATIONS
Leyli Karaçay, Zakaria Laaroussi, Sonika ujjwal, Elif Ustundag Soykan
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引用次数: 0

Abstract

With the recent advances in 5G and 6G communications and the increasing need for immersive interactions due to pandemic, new use cases such as All-Senses meeting are emerging. To realize these use cases, numerous sensors, actuators, and virtual reality devices are used. Additionally, artificial intelligence (AI) and machine learning (ML) including generative AI can be used to analyze large amount of data generated by 6G networks and devices to enable new applications and services. While AI/ML technologies are evolving, they do not have the same level of security as well-known information technology components. So, AI/ML threats and their impacts can be overlooked. On the other hand, due to inherent characteristics of AI/ML components and design of AI/ML pipeline, AI/ML services can be a target for sophisticated attacks. In order to provide a holistic security view, the effect of AI/ML components should be investigated, threats should be identified, and countermeasures should be planned. Therefore, in this study, which is an extended version of our recent study (Karaçay et al. 2023), we shed the light on the use of AI/ML services including generative large language model scenarios in All-Senses meeting use case and their security aspects by carrying out a threat modeling using the STRIDE framework and attack tree methodology. Additionally, we point out some countermeasures for identified threats.

Abstract Image

保护 6G 用例:在全感知会议上深入探讨 AI/ML 威胁
随着 5G 和 6G 通信技术的不断进步,以及大流行病对沉浸式交互的需求日益增长,全感知会议等新的用例正在出现。为实现这些用例,需要使用大量传感器、执行器和虚拟现实设备。此外,人工智能(AI)和机器学习(ML)(包括生成式人工智能)可用于分析 6G 网络和设备产生的大量数据,从而实现新的应用和服务。虽然人工智能/ML 技术在不断发展,但它们并不具备与众所周知的信息技术组件相同的安全级别。因此,AI/ML 威胁及其影响可能会被忽视。另一方面,由于 AI/ML 组件的固有特性和 AI/ML 管道的设计,AI/ML 服务可能成为复杂攻击的目标。为了提供一个全面的安全视角,应调查 AI/ML 组件的影响、识别威胁并规划应对措施。因此,本研究是我们最近研究(Karaçay et al. 2023)的扩展版本,通过使用 STRIDE 框架和攻击树方法进行威胁建模,我们揭示了全感知会议用例中人工智能/ML 服务(包括生成式大型语言模型场景)的使用及其安全方面。此外,我们还指出了针对已识别威胁的一些应对措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Annals of Telecommunications
Annals of Telecommunications 工程技术-电信学
CiteScore
5.20
自引率
5.30%
发文量
37
审稿时长
4.5 months
期刊介绍: Annals of Telecommunications is an international journal publishing original peer-reviewed papers in the field of telecommunications. It covers all the essential branches of modern telecommunications, ranging from digital communications to communication networks and the internet, to software, protocols and services, uses and economics. This large spectrum of topics accounts for the rapid convergence through telecommunications of the underlying technologies in computers, communications, content management towards the emergence of the information and knowledge society. As a consequence, the Journal provides a medium for exchanging research results and technological achievements accomplished by the European and international scientific community from academia and industry.
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