Privacy-Preserving Data Integrity Verification in Mobile Edge Computing

Mobile edge computing (MEC) is proposed as an extension of cloud computing in the scenarios where the end devices desire better services in terms of response time. Edge nodes are deployed at the proximity of the end devices, and it can pre-download parts of data stored in the cloud so that the end devices can access these data with low latency. However, because the edges are usually owned by individuals and small organizations, which have limited operation capacities for maintaining the machines, the data on the edges are easily corrupted (due to external attacks or internal hardware failures). Therefore, it is essential to verify data integrity in the MEC. We propose two Integrity Checking protocols for mobile Edge computing, called ICE-basic and ICE-batch, which are designed for the cases where the user wants to check data integrity on a single edge or multiple edges, respectively. Based on the concept of provable data possession and the technique of private information retrieval, our protocols allow a third-party verifier to check the data integrity on the edges without violating users' data privacy and query pattern privacy. We rigorously prove the security and privacy guarantees of the protocols. Furthermore, we have implemented a proof-of-concept system that runs ICE, and extensive experiments are conducted. The theoretical analysis and experimental results demonstrate the proposed protocols are efficient both in computation and communication.

I. Introduction

Cloud computing has made tremendous success in the past decade, which provides powerful, scalable, and reliable computing and storage for average users and enterprises. However, when it comes to the mobile computing, the clouds cannot meet the requirements of mobility support and low response time for many mobile applications, due to the large geographic distances between the clouds and the end devices. Mobile edge computing (MEC) [1] has been proposed as a new architecture for dealing with the issue. It pushes the computation capability and data storage from cloud to the edge nodes which are at the proximity of the end devices, such that the end devices can enjoy the computing and data access services with low latency.