Abstract
With the development of IoT devices, wearable devices are being used to record various types of information. Wearable IoT devices are attached to the user and can collect and transmit user data at all times along with a smartphone. In particular, sensitive information such as location information has an essential value in terms of privacy, and therefore some IoT devices implement data protection by introducing methods such as masking. However, masking can only protect privacy to a certain extent in logs having large numbers of recorded data. However, the effectiveness may decrease if we are linked with other information collected from within the device. Herein, a scenario-based case study on deanonymizing anonymized location information based on logs stored in wearable devices is described. As a result, we combined contextual and direct evidence from the collected information. It was possible to obtain the result in which the user could effectively identify the actual location. Through this study, not only can a deanonymized user location be identified but we can also confirm that cross-validation is possible even when dealing with modified GPS coordinates.
Highlights
With the development of IoT devices, the intimacy between device users and devices has increased
IoT technology has made people’s lives easier and more prosperous, there may be privacy issues with the information collected through such IoT devices [1]
Sensors possessed by IoT devices will become more refined and diversified, and more diverse information will be exchanged through high-performance networks
Summary
With the development of IoT devices, the intimacy between device users and devices has increased. Sensors possessed by IoT devices will become more refined and diversified, and more diverse information will be exchanged through high-performance networks. Under this situation, in the case of a wearable device attached to a person 24 h a day, there is a much greater possibility of infringing on privacy. A method for deanonymizing anonymized location information is described using a scenario studied based on an IoT device investigation. Rough four scenarios, the location information, which is sensitive information among the personal information of users, was collected or reprocessed for the development of meaningful data.
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