Research had been conducted on the security and privacy issues that were raised by the number of devices in smart homes, intricately designed internet of things.
Smart homes use a variety of gadgets which run on the internet, have security cameras, sensors, smartphones and many more. All of these devices are high-tech, it can sense all the activities and movement of the place. The question of concern in the matter is can we really trust these IoT devices? Are these devices safe to use?
David Choffnes, Associate Professor of Computer Science and Executive Director of the Cybersecurity and Privacy Institute at Northeastern University said that having such high-tech devices might be dangerous for home as it allows any computer to learn the kind of devices at home, when one is home and the area where the home is. All this information should not be leaked and therefore there’s a need for better security for better protection at home.
At the ACM Internet Measurement Conference (ACM IMC ’23) in Montreal (Canada), this week, the team’s are headed for research study, titled “In the Room Where It Happens: Characterizing Local Communication and Threats in Smart Homes”.
The paper investigated the intricacies in the dealings between 93 IoT gadgets and mobiles apps across local networks revealing unexposed security and privacy problems. Although local networks are thought to be safe places, this research identifies “threats” related to IoT devices that expose sensitive information through usual protocols such as UPnP and mDNS.
PhD student from NYU Tandon
Vijay Prakash who is also the co-author noted that their examination of the IoT Inspector’s data showed instances where thousands of smart homes including IoT devices accidently revealed PII. However, with the combination of these unique hardware addresses, UUIDs and device names into household level fingerprinting techniques, will be surpassed, because a household is more specific than a fingerprinted, inference due to these browser fingerprinting methods.
The study emphasized that the local networks’ used by IoT gadgets are not very strongly protected information that can be collected without coming into the knowledge of the user.
According to Juan Tapiador who works as a professor in UC3M, gathered data, received through an oblique methodology, allows generating dossiers about habits and social classes.
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