Enabling Robust and Privacy-Preserving Resource Allocation in Fog Computing

Abstract

Fog computing is an extension of cloud computing and enables computing directly at the edge of the network. In fog computing paradigm, the fog nodes reside between smart end devices and the cloud. Benefiting from the structure of fog computing, fog computing can provide services with low latency, location awareness, and mobility. Since the fog nodes are not as powerful as the cloud, resource allocation techniques are usually adapted to optimize the utilization of the resources of fog nodes. However, the current resource allocation techniques are not privacy-preserving, i.e., an attacker can easily find end devices’ sensitive information. In this paper, we propose a privacy-preserving resource allocation scheme for fog computing. The new proposal has constant message expansion, and it is secure against both an eavesdropper and a smart gateway that is employed to perform the resource allocation algorithm. Our scheme is also robust, since it achieves a full key compromise resistance which guarantees that even if the private keys of all the fog nodes in a fog system are corrupted the scheme remains secure.