A Survey on IoT Intrusion Detection: Federated Learning, Game Theory, Social Psychology, and Explainable AI as Future Directions

被引:74
|
作者
Arisdakessian, Sarhad [1 ]
Wahab, Omar Abdel [1 ]
Mourad, Azzam [2 ,3 ]
Otrok, Hadi [4 ]
Guizani, Mohsen [5 ]
机构
[1] Univ Quebec Outaouais, Dept Comp Sci & Engn, Gatineau, PQ J8Y 3G5, Canada
[2] Lebanese Amer Univ, Dept Comp Sci & Math, Beirut, Lebanon
[3] New York Univ Abu Dhabi, Sci Div, Abu Dhabi, U Arab Emirates
[4] Khalifa Univ, Dept EECS, Abu Dhabi, U Arab Emirates
[5] Mohamed Bin Zayed Univ Artificial Intelligence, Dept ML, Abu Dhabi, U Arab Emirates
基金
加拿大自然科学与工程研究理事会;
关键词
Internet of Things; Intrusion detection; Cloud computing; Taxonomy; Collaborative work; Game theory; Edge computing; Cybersecurity; explainable artificial intelligence (XAI); federated learning (FL); game theory; internet of Things (IoT); intrusion detection systems (IDSs); DETECTION SYSTEM; COMPREHENSIVE SURVEY; ANOMALY DETECTION; INTERNET; SECURITY;
D O I
10.1109/JIOT.2022.3203249
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the past several years, the world has witnessed an acute surge in the production and usage of smart devices which are referred to as the Internet of Things (IoT). These devices interact with each other as well as with their surrounding environments to sense, gather and process data of various kinds. Such devices are now part of our everyday's life and are being actively used in several verticals, such as transportation, healthcare, and smart homes. IoT devices, which usually are resource-constrained, often need to communicate with other devices, such as fog nodes and/or cloud computing servers to accomplish certain tasks that demand large resource requirements. These communications entail unprecedented security vulnerabilities, where malicious parties find in this heterogeneous and multiparty architecture a compelling platform to launch their attacks. In this work, we conduct an in-depth survey on the existing intrusion detection solutions proposed for the IoT ecosystem which includes the IoT devices as well as the communications between the IoT, fog computing, and cloud computing layers. Although some survey articles already exist, the originality of this work stems from the three following points: 1) discuss the security issues of the IoT ecosystem not only from the perspective of IoT devices but also taking into account the communications between the IoT, fog, and cloud computing layers; 2) propose a novel two-level classification scheme that first categorizes the literature based on the approach used to detect attacks and then classify each approach into a set of subtechniques; and 3) propose a comprehensive cybersecurity framework that combines the concepts of explainable artificial intelligence (XAI), federated learning, game theory, and social psychology to offer future IoT systems a strong protection against cyberattacks.
引用
收藏
页码:4059 / 4092
页数:34
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