INVESTIGATION OF DEEP LEARNING OPTIMIZERS FOR FALSE WINDOW SIZE INJECTION ATTACK DETECTION IN UNMANNED AERIAL VEHICLE NETWORK ARCHITECTURE

Abstract
The Unmanned Aerial Vehicle (UAV) network plays a prominent role in this pandemic era. Nowadays UAVs are applied in various applications like military, civil etc. This article works on the Search and Rescue application part. UAV networks are applied in search and rescue operations in order to find the missing people in Hill areas. Due to false data dissemination attacks some UAVs in the network will lost the data so the rescue will become an issue. In order to detect those attacks this work uses Feed Forward Neural network with backpropagation algorithm. This work experiments chosen optimizers to get the accurate detection of attack and compares the results among the optimizers All the more explicitly this examination did in the Delay-Tolerant based Decentralized Multi-Layer UAV ad-hoc organization Assisting VANET (DDMUAV) design utilizing Opportunistic Network Environment (ONE) test system.

Authors
N Vanitha1, G Padmavathi2
Avinashilingam Institute for Home Science and Higher Education for Women, India1, Avinashilingam Institute for Home Science and Higher Education for Women, India2

Keywords
Unmanned Aerial Vehicle, Delay Tolerant, Neural Network, Optimizer, Simulation
Published By :
ICTACT
Published In :
ICTACT Journal on Communication Technology
( Volume: 12 , Issue: 3 )
Date of Publication :
September 2021
DOI :

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