Energy Consumption Patterns as Indicators of Cyberattacks on Smart Home IoT Devices

The rapid adoption of Internet of Things (IoT) devices in smart homes has raised significant security concerns due to the lack of standardization and focus on security by manufacturers. This study aims to analyze the energy consumption patterns of IoT devices before and during cyberattacks, providin...

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Bibliographic Details
Published in:2024 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2024
Main Author: Suhair M.R.B.; Marbukhari N.B.; Yussoff Y.M.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201261065&doi=10.1109%2fISIEA61920.2024.10607160&partnerID=40&md5=f9ec098273336ad297a967f1b96e7f38
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Summary:The rapid adoption of Internet of Things (IoT) devices in smart homes has raised significant security concerns due to the lack of standardization and focus on security by manufacturers. This study aims to analyze the energy consumption patterns of IoT devices before and during cyberattacks, providing a potential method for detecting attacks in smart home environments. A testbed consisting of various smart home IoT devices, including a contact sensor, Google Home Mini, IP camera, and Wi-Fi bulb, was set up in a controlled laboratory environment. These devices were subjected to different types of attacks, such as ping flood, ping of death, deauthentication, and ARP spoofing, while their energy consumption levels were measured. The collected data was analyzed using the Wilcoxon signed-rank test to determine if the attacks caused a significant increase in energy consumption. The results revealed that certain attacks, particularly ping flood and deauthentication, led to substantial increases in energy consumption, with the highest increase of 113.17% observed in the contact sensor during the ping flood attack. The findings suggest that monitoring energy consumption patterns could potentially supplement existing intrusion detection systems and provide an early warning for cyberattacks in smart home networks. However, limitations related to measurement accuracy and potential sources of interference were identified, highlighting the need for further research in this area. © 2024 IEEE.
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DOI:10.1109/ISIEA61920.2024.10607160