Open AccessA Self-Adaptive and Self-Learning Methodology for Wireless Intrusion Detection using Deep Neural Network
Author(s) -
R. Sathya
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i6.4813
Subject(s) - cyber physical system , computer science , intrusion detection system , component (thermodynamics) , process (computing) , artificial neural network , point (geometry) , computation , physical system , computer security , intrusion , artificial intelligence , algorithm , physics , geometry , mathematics , quantum mechanics , thermodynamics , geology , operating system , geochemistry
Cyber physical systems combine both the physical as well as the computation process. Embedded computers and systems monitor to control the physical forms with feedback loops which have an effect on computations and contrariwise. A vast number of failures and cyber-attacks are present in the cyber physical systems, which leads to a limited growth and accuracy in the intrusion detection system and thus implementing the suitable actions which may be taken to reduce the damage to the system. As Cyber-physical systems square measure but to be made public universally, the applying of the instruction detection mechanism remains open presently. As a result, the inconvenience is made to talk about the way to suitably apply the interruption location component to Cyber physical frameworks amid this paper. By analysing the unmistakable properties of Cyber-physical frameworks, it extraordinary to diagram the exact necessities 1st. At that point, the arranging characterize of the intrusion discovery component in Cyber-physical frameworks is introduced in terms of the layers of framework and particular location procedures. At long last, a few imperative investigation issues unit known for edifying the following considers.