2022
DOI: 10.3389/fdata.2021.782902
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## Abstract:With the prompt revolution and emergence of smart, self-reliant, and low-power devices, Internet of Things (IoT) has inconceivably expanded and impacted almost every real-life application. Nowadays, for example, machines and devices are now fully reliant on computer control and, instead, they have their own programmable interfaces, such as cars, unmanned aerial vehicles (UAVs), and medical devices. With this increased use of IoT, attack capabilities have increased in response, which became imperative that new … Show more

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##### Cited by 13 publications
(7 citation statements)
##### References 43 publications
(68 reference statements)
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“…Botnet detection techniques for the IoT are either network-based or host-based [16][17][18][19][20]. However, the host-based approach is less realistic.…”
Section: Related Workmentioning
confidence: 99%
“…However, the host-based approach is less realistic. For instance, in [16,17], the authors developed a comprehensive architecture for IoT instruction detection and classification at the network layer of the IoT paradigm. Six different supervised ML methods were employed to develop the IoT-IDS: three ensemble learning methods, two neural network methods, and one kernel method.…”
Section: Related Workmentioning
confidence: 99%
“…can be implemented into the onboard computer to detect any security flaws, monitor the system's events, and report incidents that violate the security policy [19]. However, in cybersecurity, more than 99% of new intrusions are symmetrical with very small mutations of previously existing ones [20]. This requires the development of very accurate I.D.S.s with high sensitivity in detecting cyberattacks.…”
Section: Introductionmentioning
confidence: 99%
“…attacks and can threaten A.V.s' applications, systems, and network layers [11]. Generally, it is challenging to detect the FDI attack because, for example, some of its effects cannot be noticed in the short term [20].…”
Section: Introductionmentioning
confidence: 99%
“…can be implemented into the onboard computer to detect any security flaws, monitor the system's events, and report incidents that violate the security policy [19]. However, like image recognition, in cybersecurity, more than 99% of new intrusions are symmetrical with very small mutations of previously existing ones [20]. This requires the development of very accurate I.D.S.s with high sensitivity in detecting cyber-attacks.…”
Section: Introductionmentioning
confidence: 99%