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Designing and Validating a Blockchain-based Architecture to Enforce Privacy in Human Robot Interaction

Social Robots (SR) can record large streams of raw data in the form of images, audio, Radio Frequency Identiﬁcation (RFID), among other sensory sources, which could be instrumental in enforcing Human-robot interactions (HRI). However, the emotional bonds between humans and SR can raise an SR accessing/inferring profoundly private information, e.g., emotional states. Therefore, in what concerns privacy, SR may be a liability. Clarifying the ownership of data collected by robots is an issue of concern in the European Union (EU) General Data Protection Regulation (GDPR), which requires ’privacy-by-design’. The paper presents BlockRobot – a Blockchain (BC)-based software design model for developing privacy-by-design application in Human-Robot Interactions (HRI). Based on this design model, users can access the private data generated in their HRI. This paper’s contributions are the design and validation of a model to develop privacy-by-design applications for HRI. This model integrates BC technology with robots to audit robotic events such as Red, Green, Blue, Depth (RGB-D) images, and RFID tags. Smart contracts and crypto-wallets accomplish identity management. To demonstrate the utility of the initial implementation of a Decentralized Application (dApp), we implement a prototype, based on the private permissioned Evolution of Scalability (EOS) Blockchain integrated with the social robot moving in a non-laboratory environment.