Research Area:  Edge Computing

Abstract:

As the rapid development of 5G and Internet of Things (IoT) techniques, more and more mobile devices with specific sensing capabilities access to the network and large amounts of data. The traditional architecture of the cloud computing cannot satisfy the requirements, such as low latency, fast data access for IoT applications. Mobile edge computing (MEC) can solve these problems, and improve the execution efficiency of the system. In this paper, we propose a privacy preserving data aggregation scheme for MEC assisted IoT applications. In our model, there are three participants, i.e., terminal device (TD), edge server (ES), and public cloud center (PCC). The data generated by the TDs is encrypted and transmitted to the ES, then the ES aggregates the data of the TDs and submits the aggregated data to the PCC. At last, the aggregated plaintext data can be recovered by PCC through its private key. Our scheme not only guarantees data privacy of the TDs but also provides source authentication and integrity. Compared with traditional model, our scheme can save half of communication cost, and is very suitable for MEC assisted IoT applications.

Keywords:  

Author(s) Name:  Xiong Li; Shanpeng Liu; Fan Wu; Saru Kumari and Joel J. P. C. Rodrigues

Publisher name:  IEEE

DOI:  10.1109/JIOT.2018.2874473

Volume Information:  Volume: 6, Issue: 3, June 2019,Page(s): 4755 - 4763

Paper Link:   https://ieeexplore.ieee.org/document/8485416