Querying in Internet of Things with Privacy Preserving: Challenges, Solutions and Opportunities
Abstract
IoT is envisioned as the next stage of the information revolution, enabling various daily applications and providing better service by conducting a deep fusion with cloud and fog computing. As the key mission of most IoT applications, data management, especially the fundamental function-data query, has long been plagued by severe security and privacy problems. Most query service providers, including the big ones (e.g., Google, Facebook, Amazon, and so on) are suffering from intensive attacks launched by insiders or outsiders. As a consequence, processing various queries in IoT without compromising the data and query privacy is an urgent and challenging issue. In this article, we propose a thing-fog-cloud architecture for secure query processing based on well studied classical paradigms. Following with a description of crucial technical challenges in terms of functionality, privacy and efficiency assurance, we survey the latest milestone-like approaches, and provide an insight into the advantages and limitations of each scheme. Based on the recent advances, we also discuss future research opportunities to motivate efforts to develop practical private query protocols in IoT.
Publication Title
IEEE Network
Recommended Citation
Ren, H., Li, H., Dai, Y., Yang, K., & Lin, X. (2018). Querying in Internet of Things with Privacy Preserving: Challenges, Solutions and Opportunities. IEEE Network, 32 (6), 144-151. https://doi.org/10.1109/MNET.2018.1700374
