Towards improving explainability, resilience and performance of cybersecurity analysis of 5G/IoT networks (work-in-progress paper)

Manh-Dung Nguyen, Vinh Hoa La, A. Cavalli, Edgardo Montes de Oca
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引用次数: 1

Abstract

Artificial Intelligence (AI) is envisioned to play a critical role in controlling and orchestrating 5G/IoT networks and their applications, thanks to its capabilities to recognize abnormal patterns in complex situations and produce accurate decisions. However, AI models are vulnerable to adversarial attacks, thus the societal view is far from trustworthy as to its usage in safety critical areas relying on 5G/IoT networks. In this paper, we present ongoing work being done in the H2020 SPATIAL project that targets developing and evaluating AI-based modules for anomaly detection and Root Cause Analysis in the 5G/IoT context regarding different criteria, such as explainability, resilience and performance on a real 5G/IoT testbed.
提高5G/物联网网络安全分析的可解释性、弹性和性能(正在研究的文件)
人工智能(AI)有望在控制和协调5G/物联网网络及其应用方面发挥关键作用,因为它能够识别复杂情况下的异常模式并产生准确的决策。然而,人工智能模型容易受到对抗性攻击,因此社会对其在依赖5G/物联网网络的安全关键领域的使用的看法远不值得信赖。在本文中,我们介绍了H2020空间项目中正在进行的工作,该项目旨在开发和评估基于人工智能的模块,用于5G/物联网背景下的异常检测和根本原因分析,涉及不同的标准,如可解释性、弹性和真实5G/物联网测试平台上的性能。
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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