Why not keep your personal data secure yet private in IoT?: Our lightweight approach

Abstract

IoT (Internet of Things) systems are resource-constrained and primarily depend on sensors for contextual, physiological and behavioral information. Sensitive nature of sensor data incurs high probability of privacy breaching risk due to intended or malicious disclosure. Uncertainty about privacy cost while sharing sensitive sensor data through Internet would mostly result in overprovisioning of security mechanisms and it is detrimental for IoT scalability. In this paper, we propose a novel method of optimizing the need for IoT security enablement, which is based on the estimated privacy risk of shareable sensor data. Particularly, our scheme serves two objectives, viz. privacy risk assessment and optimizing the secure transmission based on that assessment. The challenges are, firstly, to determine the degree of privacy, and evaluate a privacy score from the fine-grained sensor data and, secondly, to preserve the privacy content through secure transfer of the data, adapted based on the measured privacy score. We further meet this objective by introducing and adapting a lightweight scheme for secure channel establishment between the sensing device and the data collection unit/ backend application embedded within CoAP (Constrained Application Protocol), a candidate IoT application protocol and using UDP as a transport. We consider smart energy management, a killer IoT application, as the use-case where smart energy meter data contains private information about the residents. Our results with real household smart meter data demonstrate the efficacy of our scheme.