Cognitive Lightweight Logistic Regression-Based IDS for IoT-Enabled FANET to Detect Cyberattacks

Table 1

Intrusion detection system for UAV networks.

Reference	Authors	Field of study	Type of IDS	Description
[16]	Bouhamed et al.	UAV network	Signature	Deep reinforcement learning IDS is formulated to detect possible security attacks
[17]	Shrestha et al.	UAV network	Signature	UAV-based IDS is designed using machine learning where decision tree approach given the optimal results in terms of accuracy
[18]	Amouri et al.	Mobile Internet of things (M-IoT)	Signature	Two different mobility models are used which include random way point and Gauss–Markov while designing IDS for mobile IoTs. DDoS and black hole attacks are easily detected with 98% high power velocity
[19]	Khan et al.	Internet of things	Signature	Deep learning-based IDS is implemented for IoT to detect MITM, DDoS, and DoS
[20]	Ghaleb et al.	Vehicular ad hoc networks (VANETs)	Signature	Machine learning algorithms are used to propose IDS for VANETs using NSL-KDD data set