IJBTT

Black Box Logging System for Drones

	International Journal of Computer Trends and Technology (IJCTT)
	© 2019 by IJCTT Journal
	Volume-67 Issue-3
	Year of Publication : 2019
	Authors : Smrithi.S, Ms.Vijayalakshmi .R, Dr.Veeralakshmi.P
	DOI :  10.14445/22312803/IJCTT-V67I3P104

MLA Style: Smrithi.S, Ms.Vijayalakshmi .R, Dr.Veeralakshmi.P, "Black Box Logging System for Drones" International Journal of Computer Trends and Technology 67.3 (2019): 13-18.

APA Style:Smrithi.S, Ms.Vijayalakshmi .R, Dr.Veeralakshmi.P, (2019). Black Box Logging System for Drones. International Journal of Computer Trends and Technology, 67(3), 13-18.

Abstract
Unmanned aerial vehicles (UAVs) like drones are in dire need of efficient data retrieval and regular updates. This project aims to create a software use a fully autonomous system for the effective functioning of drones either implicitly or partially independent of human control. The implementation is done by providing access only to any one of two designated aviation controller who is given with an irreplaceable token by the Administrator at a time using an asymmetric cryptographic algorithm-RSA Algorithm. This algorithm ensures the avoidance of vulnerability to the drone system. The goal of the proposed research architecture is to provide the recovery mechanism for the obstacles encountered by the drones in the real-time scenarios and momentary payload information. This approach will be further evolved based on adaptive learning software (SCENGEN) to facilitate the drones with appropriate solutions for wisely dealing with the security attacks such as repudiation, masquerade during its fly time. The drone’s momentary payload information is gathered with respect to three scenarios namely: Target Reached, Midway Hurdle encountered and Hacking of drone control is finally embedded in the Black Box cloud.

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Keywords
Unmanned Aerial Vehicles (UAVs), Adaptive Learning, Artificial Intelligence Cryptography and network security, Deep Learning, Database and Cloud computing.