AI-Driven Cybersecurity Threats to Future Networks

被引:3
|
作者
Senouci, Sidi-Mohammed [1 ,2 ]
Sedjelmaci, Hichem [3 ,4 ]
Liu, Jiajia [5 ]
Rehmani, Mubashir Husain [6 ]
Bou-Harb, Elias [7 ]
机构
[1] Univ Paris XI, Comp Sci, Orsay, France
[2] Inst Natl Polytech Toulouse, Toulouse, France
[3] Orange Labs, Cybersecur & Artificial Intelligence AI, Lannion, France
[4] Orange Labs, Lannion, France
[5] Northwestern Polytech Univ, Sch Cybersecur, Xian, Shaanxi, Peoples R China
[6] Cork Inst Technol, Dept Comp Sci, Cork, Ireland
[7] Univ Texas San Antonio, Cyber Ctr Secur & Analyt, San Antonio, TX USA
来源
IEEE VEHICULAR TECHNOLOGY MAGAZINE | 2020年 / 15卷 / 03期
关键词
D O I
10.1109/MVT.2020.3007981
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The articles in this special section focus on artificial intelligence-driven cybersecurity threats to future networks. Future-generation networks (5G and beyond 5G) will include a variety of services for various verticals, such as enhanced mobile broadband, health monitoring, Industry 4.0, smart energy distribution, and automotive networks. These vertical services and the critical components that comprise 5G architecture (e.g., radio access and edge and core networks) exhibit several cybersecurity vulnerabilities that attract attackers to use all their capabilities to exploit and hence shut down these networks. Recently, a new generation of smart threats, defined as artificial intelligence (AI ) attacks, has appeared. These smart attacks either turn AI into weapons to attack 5G services or hack the AI algorithms used by 5G components. In the first misbehavior, attackers take advantage of AI's improved ability to launch lethal and stealthy threats against attractive targets, e.g., autonomous vehicles, drones, or manufacturing machinery. In the second misbehavior, attackers hack machine learning (ML) algorithms by modifying, for instance, the labels of the ML classification functions and altering the training data, causing a decrease in the accuracy of the classification rate. © 2020 IEEE.
引用
收藏
页码:5 / 6
页数:2
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