Journal
SENSORS
Volume 21, Issue 5, Pages -Publisher
MDPI
DOI: 10.3390/s21051809
Keywords
Internet of Things (IoT); machine learning; deep learning; intrusion detection system; wireless sensor network; testbed
Funding
- Ministry of Science and Technology, Taiwan
- MOST [108-2410-H-161-004]
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The rapid growth of IoT has unlocked the vision of a smart world but also raised significant security concerns. The research focuses on intrusion detection systems, analyzes various threats, discusses healthcare applications and security issues in IoT, and addresses research challenges for dealing with anomalies effectively.
The escalated growth of the Internet of Things (IoT) has started to reform and reshape our lives. The deployment of a large number of objects adhered to the internet has unlocked the vision of the smart world around us, thereby paving a road towards automation and humongous data generation and collection. This automation and continuous explosion of personal and professional information to the digital world provides a potent ground to the adversaries to perform numerous cyber-attacks, thus making security in IoT a sizeable concern. Hence, timely detection and prevention of such threats are pre-requisites to prevent serious consequences. The survey conducted provides a brief insight into the technology with prime attention towards the various attacks and anomalies and their detection based on the intelligent intrusion detection system (IDS). The comprehensive look-over presented in this paper provides an in-depth analysis and assessment of diverse machine learning and deep learning-based network intrusion detection system (NIDS). Additionally, a case study of healthcare in IoT is presented. The study depicts the architecture, security, and privacy issues and application of learning paradigms in this sector. The research assessment is finally concluded by listing the results derived from the literature. Additionally, the paper discusses numerous research challenges to allow further rectifications in the approaches to deal with unusual complications.
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