Deep learning and big data technologies for IoT security

被引:176
|
作者
Amanullah, Mohamed Ahzam [1 ]
Habeeb, Riyaz Ahamed Ariyaluran [2 ,3 ]
Nasaruddin, Fariza Hanum [3 ]
Gani, Abdullah [4 ,5 ]
Ahmed, Ejaz [5 ]
Nainar, Abdul Salam Mohamed [6 ]
Akim, Nazihah Md [2 ]
Imran, Muhammad [7 ]
机构
[1] Telekom Res & Dev Sdn Bhd, Res & Innovat Dev, Cyberjaya, Selangor, Malaysia
[2] Int Univ Malaya Wales, Fac Sci Technol Engn & Math, Kuala Lumpur, Malaysia
[3] Univ Malaya, Fac Comp Sci & Informat Technol, Dept Informat Syst, Kuala Lumpur, Malaysia
[4] Univ Malaysia Sabah, Fac Comp & Informat, Kota Kinabalu, Sabah, Malaysia
[5] Univ Malaya, Ctr Res Mobile Cloud Comp, Kuala Lumpur, Malaysia
[6] Greenview Islamic Int Sch, Shah Alam, Selangor, Malaysia
[7] King Saud Univ, Coll Appl Comp Sci, Riyadh, Saudi Arabia
关键词
Deep learning; Big data; IoT security; INTRUSION DETECTION; ATTACK DETECTION; NEURAL-NETWORK; DATA ANALYTICS; ANOMALY DETECTION; ROUTING ATTACKS; APACHE SPARK; INTERNET; FRAMEWORK; AUTHENTICATION;
D O I
10.1016/j.comcom.2020.01.016
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Technology has become inevitable in human life, especially the growth of Internet of Things (IoT), which enables communication and interaction with various devices. However, IoT has been proven to be vulnerable to security breaches. Therefore, it is necessary to develop fool proof solutions by creating new technologies or combining existing technologies to address the security issues. Deep learning, a branch of machine learning has shown promising results in previous studies for detection of security breaches. Additionally, IoT devices generate large volumes, variety, and veracity of data. Thus, when big data technologies are incorporated, higher performance and better data handling can be achieved. Hence, we have conducted a comprehensive survey on state-of-the-art deep learning, IoT security, and big data technologies. Further, a comparative analysis and the relationship among deep learning, IoT security, and big data technologies have also been discussed. Further, we have derived a thematic taxonomy from the comparative analysis of technical studies of the three aforementioned domains. Finally, we have identified and discussed the challenges in incorporating deep learning for IoT security using big data technologies and have provided directions to future researchers on the IoT security aspects.
引用
收藏
页码:495 / 517
页数:23
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