Detection of Malicious Nodes in Flying Ad-hoc Network with Supervised Machine Learning
Linear Regression; Logistic Regression; Node Existence Matrix; Node Reputation Matrix; Path Reputation Matrix
An Ad-hoc network (FANET) is a new upcoming technology which has been used in several sectors. Ad-hoc networks are mostly wireless local area networks (LANs). The devices communicate with each other directly instead of relying on a base station or access points as in wireless LANs for data transfer. In an Ad-hoc network the communication between one node to another in a FANET is not secured and there isn't any authorized protocol for secured communication. Therefore, we suggest an algorithm to detect the malicious node in a network. This algorithm uses Linear regression to calculate the reputation or trust value of a node in the network. Then the above found trust value is used to classify the node as normal node or malicious node based on the Logistic Regression Classification. Thus, allowing a secure communication of data and avoiding attacks. 2022 IEEE.
Tangade S.; Kumaar R.A.; Malavika S.; Monisha S.; Azam F.
Proceedings of the 3rd International Conference on Smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2022
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICSTCEE56972.2022.10099989 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158131076&doi=10.1109%2fICSTCEE56972.2022.10099989&partnerID=40&md5=a4bb8e8bb030b88bd265a3ed7fc1ce39
Tangade S., CHRIST University, Dept. of CSE., Bengaluru, India; Kumaar R.A., School of ECE, REVA University, Bengaluru, India; Malavika S., School of ECE, REVA University, Bengaluru, India; Monisha S., School of ECE, REVA University, Bengaluru, India; Azam F., School of Comp. Science and Engineering, REVA University, Bengaluru, India