Open AccessMitigating DoS attacks in IoT using Supervised and Unsupervised Algorithms – A Survey
Author(s) -
S.B. Gopal,
P. Chinnasamy,
D. Nanthiya,
R. Snega Priya,
G. Saran,
M. Sathya Priya
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1055/1/012072
Subject(s) - computer science , internet of things , power consumption , computer security , order (exchange) , multidisciplinary approach , artificial intelligence , work (physics) , machine learning , algorithm , power (physics) , engineering , mechanical engineering , social science , physics , finance , quantum mechanics , sociology , economics
IoT is an evolving technology used in enormous applications in order to reduce the human intervention. As IoT is used in hybrid environment where it has to enable communication between multidisciplinary components it is facing lot more challenges. Security is the main issue had to be addressed. IoT devices are with limited power consumption; hence it’s not possible implement existing security algorithms as it is. Security attacks are increasing day by day; hence the dynamic solution has to be given rather than static solution. Machine learning is a promised technology that can be used in order to solve the security issues. This paper list out various work so far carried out in the area of machine learning for IoT security and solutions provided with future direction of research in this area.