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The large spread of sensors and smart devices in urban infrastructures aremotivating research in the area of Internet of Thing (IoT), to develop newservices and improve citizens' quality of life. Sensors and smart devicesgenerate large amount of measurement data from sensing the environment, whichis used to enable services, such as control power consumption or trafficdensity. To deal with such a large amount of information, and provide accuratemeasurements, service providers can adopt information fusion, which, given thedecentralized nature of urban deployments, can be performed by means ofconsensus algorithms. These algorithms allow distributed agents to(iteratively) compute linear functions on the exchanged data, and takedecisions based on the outcome, without the need for the support of a centralentity. However, the use of consensus algorithms raises several securityconcerns, especially when private or security critical information are involvedin the computation. This paper proposes ODIN, a novel algorithm that allowsinformation fusion over encrypted data. ODIN is a privacy-preserving extensionof the popular consensus gossip algorithm, that prevents distributed agentshave direct access to the data while they iteratively reach consensus; agentscannot access even the final consensus value, but can only retrieve partialinformation, e.g., a binary decision. ODIN uses efficient additive obfuscationand proxy re-encryption during the update steps, and Garbled Circuits to takefinal decisions on the obfuscated consensus. We discuss the security of ourproposal, and show its practicability and efficiency on real-world resourceconstrained devices, developing a prototype implementation for Raspberry Pidevices.

ODIN: Obfuscation-based privacy preserving consensus algorithm for Decentralized Information fusion in smart device Networks