%0 Journal Article
%T A Hybrid Intrusion Detection System for Smart Home Security Based on Machine Learning and User Behavior
%A Faisal Alghayadh
%A Debatosh Debnath
%J Advances in Internet of Things
%P 10-25
%@ 2161-6825
%D 2021
%I Scientific Research Publishing
%R 10.4236/ait.2021.111002
%X With
technology constantly becoming present in people¡¯s lives, smart homes are
increasing in popularity. A smart home system controls lighting, temperature, security
camera systems, and appliances. These devices and sensors are connected to the
internet, and these devices can easily become the target of attacks. To
mitigate the risk of using smart home devices, the security and privacy thereof
must be artificially smart so they can adapt based on user behavior and environments.
The security and privacy systems must accurately analyze all actions and predict
future actions to protect the smart home system. We propose a Hybrid Intrusion Detection
(HID) system using machine  learning algorithms, including random forest, X gboost,
decision tree, K -nearest neighbors, and misuse detection technique.
%K Anomaly Detection
%K Smart Home Systems
%K Behavioral Patterns
%K Security
%K Threats
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=106859