Metadata-Private Resource Allocation in Edge Computing Withstands Semi-Malicious Edge Nodes

TL;DR

This paper introduces a secure resource allocation method for edge computing that protects task metadata from being exposed or exploited by semi-malicious edge nodes.

Contribution

A novel resource allocation scheme using searchable encryption and zero-knowledge proofs to ensure metadata privacy and resist semi-malicious edge nodes.

Findings

The proposed scheme formally satisfies required security concepts.

Experimental results demonstrate the effectiveness of the metadata privacy protection method.

The approach resists privacy breaches from corrupted edge nodes and eavesdroppers.

Abstract

Edge computing provides higher computational power and lower transmission latency by offloading tasks to nearby edge nodes with available computational resources to meet the requirements of time-sensitive tasks and computationally complex tasks. Resource allocation schemes are essential to this process. To allocate resources effectively, it is necessary to attach metadata to a task to indicate what kind of resources are needed and how many computation resources are required. However, these metadata are sensitive and can be exposed to eavesdroppers, which can lead to privacy breaches. In addition, edge nodes are vulnerable to corruption because of their limited cybersecurity defenses. Attackers can easily obtain end-device privacy through unprotected metadata or corrupted edge nodes. To address this problem, we propose a metadata privacy resource allocation scheme that uses searchable encryption to protect metadata privacy and zero-knowledge proofs to resist semi-malicious edge nodes. We have formally proven that our proposed scheme satisfies the required security concepts and experimentally demonstrated the effectiveness of the scheme.

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