Privacy-preserving IoT Data Sharing Scheme -- 2022 IEEE 13th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)

Internet of Things (IoT) empowers us to connect physical objects ranging from smart buildings to portable intelligent devices, such as IoT wearable devices. The principal advantages of IoT wearable devices are allowing us remotely to collect data and also giving us the capability to control and monitor objects. These features can be utilized in various ways, such as establishing a connection, locating devices, authenticating users, protect users' privacy, sharing data and which is central to this proposed paper. Data sharing is receiving a widespread application in our daily lives since it facilitates cooperation between two ends, e.g., User-to-User, User-to-Devices, Devices-to-Devices, etc, and provides services to both ends or one of them. Data sharing can be granted using different factors, one of which is something in a user's/an IoT device's environment which is in this paper broadcast signals. Using broadcast signals to measure Received Signal Strength Indicator (RSSI) values and Machine Learning (ML) models, this paper implements an IoT data sharing scheme based on something that is in a user's/an IoT device's environment. The proposed scheme is experimentally tested using different ML models and shows 97.78% as its highest accuracy.

Privacy-preserving IoT Data Sharing Scheme -- 2022 IEEE 13th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Academic Article