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Wireless Interference Analysis for Home IoT Security Vulnerability Detection
Abstract
The integrity of wireless networks that make up the clear majority of IoT networks lack the inherent security of their wired counterparts. With the growth of the internet of things (IoT) and its pervasive nature in the modern home environment, it has caused a spike in security concerns over how the network infrastructure handles, transmits, and stores data. New wireless attacks such as KeySniffer and other attacks of this type cannot be tracked by traditional solutions. Therefore, this study investigates if wireless spectrum frequency monitoring using interference analysis tools can aid in the monitoring of device signals within a home IoT network. This could be used enhance the security compliance guidelines set forth by OWASP and NIST for these network types and the devices associated. Active and passive network scanning tools are used to provide analysis of device vulnerability and as comparison for device discovery purposes. The work shows the advantages and disadvantages of this signal pattern testing technique compared to traditional network scanning methods. The authors demonstrate how RF spectrum analysis is an effective way of monitoring network traffic over the air waves but also possesses limitations in that knowledge is needed to decipher these patterns. This article demonstrates alternative methods of interference analysis detection.
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