Abstract
A defining characteristic of the Internet of Things (IoT) is pervasive collection and linkage of user data to provide personalised experiences. To enable this functionality, IoT devices and services must be connected and share data about users’ interactions with multiple nodes in the network. Consistent identification of users and devices across the network is likewise necessary. These aspects of the IoT can pose risks to user privacy. Potentially invasive inferences can be drawn from linked datasets, including data generated through usage of connected devices and services. The forthcoming General Data Protection Regulation (GDPR) contains numerous provisions relevant to the risks posed by identification technologies. However, the strict legal requirements defined in the Articles of the GDPR may be insufficient to ensure a fair balance is struck between user’s interests in privacy and the interests of IoT developers and data controllers. To address this gap, this paper proposes a three-step transparency model based on known privacy risks of the IoT, weaknesses in relevant legally binding provisions in the GDPR, and the GDPR’s governing principles. Eleven guidelines aimed at IoT developers and data controllers are described addressing how information about the functionality of IoT devices and services should be shared with users. The guidelines describe ethically desirable standards to be adhered to in addition to the GDPR’s legally binding requirements. To demonstrate how the guidelines could apply in practice and alter the design choices and practices of IoT developers and data controllers, connected cars are considered as a use case. © 2018 Institution of Engineering and Technology. All rights reserved.