TY - GEN
T1 - A Tagging Solution to Discover IoT Devices in Apartments
AU - Kaplan, Berkay
AU - Lopez-Toledo, Israel J.
AU - Gunter, Carl
AU - Qian, Jingyu
N1 - We would like to thank Hyun Bin Lee for participating in our discussion and finding related papers to our project. His insights were very valuable and helped us understand the field.
PY - 2023/12/4
Y1 - 2023/12/4
N2 - The number of Internet of Things (IoT) devices in smart homes is increasing. This broad adoption facilitates users' lives, but it also brings problems. One such issue is that some IoT devices may invade users' privacy through obscure data collection practices or hidden devices. Specific IoT devices can exist out of sight and still collect user data to send to third parties via the Internet. Owners can easily forget the location or even the existence of these devices, especially if the owner is a landlord managing several properties. The landlord-owner scenario creates multi-user problems as designers typically build IoT devices for single users. We developed tag models that use wireless protocols, buzzers, and LED lighting to guide users toward the hidden device in shared spaces and accommodate multi-user scenarios. They are attached to IoT devices inside a residential unit during their installation to be later discovered by a tenant. These tags are similar to Tile models or Airtag but have different features based on our privacy use case. For instance, our tags do not require pairing; multiple users can interact with them through our Android application. Our tags can also embed the IoT device's information while protecting against unwanted access to that information through a proximity requirement. Researchers have developed several other tools, such as thermal cameras or virtual reality (VR), for discovering devices, but we focused on wireless technologies. We measured specific performance metrics of our tags to analyze their feasibility for this problem. We also conducted a user study to measure the participants' comfort levels while finding objects with our tags attached. Our results indicate that wireless tags can be viable for device tracking in residential properties.
AB - The number of Internet of Things (IoT) devices in smart homes is increasing. This broad adoption facilitates users' lives, but it also brings problems. One such issue is that some IoT devices may invade users' privacy through obscure data collection practices or hidden devices. Specific IoT devices can exist out of sight and still collect user data to send to third parties via the Internet. Owners can easily forget the location or even the existence of these devices, especially if the owner is a landlord managing several properties. The landlord-owner scenario creates multi-user problems as designers typically build IoT devices for single users. We developed tag models that use wireless protocols, buzzers, and LED lighting to guide users toward the hidden device in shared spaces and accommodate multi-user scenarios. They are attached to IoT devices inside a residential unit during their installation to be later discovered by a tenant. These tags are similar to Tile models or Airtag but have different features based on our privacy use case. For instance, our tags do not require pairing; multiple users can interact with them through our Android application. Our tags can also embed the IoT device's information while protecting against unwanted access to that information through a proximity requirement. Researchers have developed several other tools, such as thermal cameras or virtual reality (VR), for discovering devices, but we focused on wireless technologies. We measured specific performance metrics of our tags to analyze their feasibility for this problem. We also conducted a user study to measure the participants' comfort levels while finding objects with our tags attached. Our results indicate that wireless tags can be viable for device tracking in residential properties.
KW - IoT
KW - Privacy
KW - Smart Homes
KW - Wireless
UR - https://www.scopus.com/pages/publications/85180155980
UR - https://www.scopus.com/pages/publications/85180155980#tab=citedBy
U2 - 10.1145/3627106.3627108
DO - 10.1145/3627106.3627108
M3 - Conference contribution
AN - SCOPUS:85180155980
T3 - ACM International Conference Proceeding Series
SP - 205
EP - 215
BT - Proceedings - 39th Annual Computer Security Applications Conference, ACSAC 2023
PB - Association for Computing Machinery
T2 - 39th Annual Computer Security Applications Conference, ACSAC 2023
Y2 - 4 December 2023 through 8 December 2023
ER -