Review of artificial intelligence for enhancing intrusion detection in the internet of things

被引：53
作者：
Saied, Mohamed [1 ]
Guirguis, Shawkat [1 ]
Madbouly, Magda [1 ]
机构：
[1] Inst Grad Studies & Res, Alexandria, Egypt
来源：
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2024年 / 127卷
关键词：
Internet of things; Intrusion detection system; Security; Artificial intelligence; Machine learning; Deep learning; Evolutionary computing; PARTICLE SWARM OPTIMIZATION; DETECTION SYSTEM; NEURAL-NETWORK; IOT; MACHINE; ATTACKS; MODEL; ANALYTICS; SECURITY; SUPPORT;
D O I：
10.1016/j.engappai.2023.107231
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Internet of Things is shaping the quality of living standard. With the rapid growth and expansion of adopting IoTbased approaches, their security represents a growing challenge for both manufacturers and consumers. There is a recent rising trend towards employing artificial intelligence approaches to enhance the security of IoT infrastructure. This survey paper focuses on reviewing recent developments in applying artificial intelligence to intrusion detection in the IoT domain. Selected articles are classified according to the applied AI algorithm. This study provides an in-depth survey highlighting the recent advances in artificial intelligence for improving the security of IoT. It summarizes and organizes the recent related research, then presents a comprehensive discussion on research challenges, open issues, and needed future research.
引用
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页数：21
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