Advancements in Intrusion Detection Systems for Internet of Things Using Machine Learning

被引：0
|
作者：
Ul Haq, Shahid [1 ]
Abbas, Ash Mohammad [1 ]
机构：
[1] Aligarh Muslim Univ, Zakir Hussain Coll Engn & Technol, Dept Comp Engn, Aligarh 202002, Uttar Pradesh, India
来源：
2022 5TH INTERNATIONAL CONFERENCE ON MULTIMEDIA, SIGNAL PROCESSING AND COMMUNICATION TECHNOLOGIES (IMPACT) | 2022年
关键词：
Intrusion detection; IoT; machine learning; IOT;
D O I：
10.1109/IMPACT55510.2022.10029002
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Advancement in technology leads to connecting different types of devices or things to the Internet and enables the formation of a special kind of network called the Internet of Things (IoT). Intrusion detection in an IoT is a challenging task due to its unique characteristics. Machine learning schemes possess the potential to improve intrusion detection systems in case of an IoT. In this paper, we present a survey of advancements in research on the use of machine learning approaches for intrusion detection in an IoT. Our focus is on architectures, schemes, and the types of machine learning approaches used for intrusion detection. We compare different schemes based on their basis and features.
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页数：5
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