Open AccessAn Intrusion Detection System in IoT Environment Using KNN and SVM Classifiers
Author(s) -
Abdulmalik M Alfarshouti,
Saad Almutairi
Publication year - 2022
Publication title -
webology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.259
H-Index - 18
ISSN - 1735-188X
DOI - 10.14704/web/v19i1/web19231
Subject(s) - denial of service attack , computer science , intrusion detection system , computer security , support vector machine , internet of things , government (linguistics) , the internet , artificial intelligence , world wide web , linguistics , philosophy
IoT applications are now used in most applications in this world to facilitate data collection and remote and automatic management of all modern devices. Due to the large spread of these devices in multiple regions, they become easily vulnerable to penetration by many types of attacks. This research will focus on network layer denial of service (DOS) attacks to detect. This type of attack was chosen because of its danger to the availability of services, such as e-commerce services, financial and government services, as well as educational organizations. Failure to provide these services frequently leads to huge financial losses in addition to loss of confidence in these organizations. Machine learning techniques will be used in the proposed research to detect these attacks in a fast and efficient manner.