k-Anonymous Query Scheme on the Internet of Things: a Zero Trust Architecture

Abstract

The paper investigates query-anonymity in Internet of things (IoT) formed by a sensor cloud, where the sensor nodes provide services of sensing and are subject to user queries of sensing data. Due to the heterogeneity and multi-carrier natures of the sensor cloud, user privacy could be impaired when the queries have to go through nodes of a third party. Thus, the paper firstly introduces a novel query k-anonymity scheme that countermeasures such a privacy threat. Based on the proposed k-anonymity scheme, the trade-offs between the achieved query-anonymity and various performance measures including, communication-cost, return-on-investment metric, path-length, and location anonymity metrics, are analyzed. By adopting a hybrid approach that takes into account the average and worst-case analysis, our evaluation results show that most of the obtained bounds on various performance anonymity trade-offs can be expressed precisely in terms of the offered level-of-anonymity k and network diameter d.