Combining Edge Computing-Assisted Internet of Things Security with Artificial Intelligence: Applications, Challenges, and Opportunities

被引:7
|
作者
Rupanetti, Dulana [1 ]
Kaabouch, Naima [1 ,2 ]
机构
[1] Univ North Dakota, Sch Elect Engn & Comp Sci, Grand Forks, ND 58202 USA
[2] Univ North Dakota, Artificial Intelligence Res AIR Ctr, Grand Forks, ND 58202 USA
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 16期
关键词
edge computing; internet of things (IoT); artificial intelligence (AI); machine learning; deep learning; cybersecurity; trust measurement; data privacy; DATA ANALYTICS; SYSTEMATIC LITERATURE; SERVICE PLACEMENT; IOT; FRAMEWORK; BLOCKCHAIN; THREATS; SCHEME; OPTIMIZATION; ARCHITECTURE;
D O I
10.3390/app14167104
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The integration of edge computing with IoT (EC-IoT) systems provides significant improvements in addressing security and privacy challenges in IoT networks. This paper examines the combination of EC-IoT and artificial intelligence (AI), highlighting practical strategies to improve data and network security. The published literature has suggested decentralized and reliable trust measurement mechanisms and security frameworks designed explicitly for IoT-enabled systems. Therefore, this paper reviews the latest attack models threatening EC-IoT systems and their impacts on IoT networks. It also examines AI-based methods to counter these security threats and evaluates their effectiveness in real-world scenarios. Finally, this survey aims to guide future research by stressing the need for scalable, adaptable, and robust security solutions to address evolving threats in EC-IoT environments, focusing on the integration of AI to enhance the privacy, security, and efficiency of IoT systems while tackling the challenges of scalability and resource limitations.
引用
收藏
页数:25
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