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An Improved Intrusion Detection Scheme in a Smart Home Environment

by Samuel Mtswenem Vanen, Sever Kwaghbee, Vershima Iyorter, Tivlumun Ge, Adekunle Adedotun Adeyelu
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 74
Year of Publication: 2025
Authors: Samuel Mtswenem Vanen, Sever Kwaghbee, Vershima Iyorter, Tivlumun Ge, Adekunle Adedotun Adeyelu
10.5120/ijca2025924607

Samuel Mtswenem Vanen, Sever Kwaghbee, Vershima Iyorter, Tivlumun Ge, Adekunle Adedotun Adeyelu . An Improved Intrusion Detection Scheme in a Smart Home Environment. International Journal of Computer Applications. 186, 74 ( Mar 2025), 42-53. DOI=10.5120/ijca2025924607

@article{ 10.5120/ijca2025924607,
author = { Samuel Mtswenem Vanen, Sever Kwaghbee, Vershima Iyorter, Tivlumun Ge, Adekunle Adedotun Adeyelu },
title = { An Improved Intrusion Detection Scheme in a Smart Home Environment },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2025 },
volume = { 186 },
number = { 74 },
month = { Mar },
year = { 2025 },
issn = { 0975-8887 },
pages = { 42-53 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number74/an-improved-intrusion-detection-scheme-in-a-smart-home-environment/ },
doi = { 10.5120/ijca2025924607 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-03-25T22:41:41.142801+05:30
%A Samuel Mtswenem Vanen
%A Sever Kwaghbee
%A Vershima Iyorter
%A Tivlumun Ge
%A Adekunle Adedotun Adeyelu
%T An Improved Intrusion Detection Scheme in a Smart Home Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 74
%P 42-53
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The fast increase in the number of Internet of Things (IoT) devices in smart homes makes them more exposed to cybersecurity threats. In turn, this creates an urgent need for robust intrusion detection systems. This study proposes an IoT Smart Home Multi User Access Control Intrusion Detection System (SHMUACIDS), with a view to improving the security by more efficiently detecting anomalies. It was designed based on a multi-layer architecture that consists of a Packet Capture Layer, a Feature Extraction Layer, the Machine Learning Model, and the Alerting System, all knitted together to work in tandem for proactively meeting the security challenges in IoT smart home environments. Intrusion Detection Data were obtained from kaggle website containing list of simulated TCP/IP connections were employed in training different machine learning models. The methodology also embeds digital signatures and proper key management, data integrity countermeasures together with an alert system which immediately notifies administrators on the detected anomalies. Results indicated that SHMUACIDS considerably outperformed the detection of anomalous activities in smart home IoT environments compared to some classical methods and previous studies. This holistic approach makes SHMUACIDS competitive in the smart home cybersecurity landscape.

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Index Terms

Computer Science
Information Sciences

Keywords

Internet of Things Intrusion Detection Machine Learning Attacks Smart Home key management Access control

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