Public-key cryptography

Computer network

Paillier cryptosystem

Data aggregator

Operating system

Distributed computing

Information privacy

Enhanced Data Rates for GSM Evolution

Encryption

Homomorphic encryption

Wireless sensor network

Set (abstract data type)

Programming language

Edge computing

Overhead (engineering)

Computer science

Cloud computing

Verifiable secret sharing

Security analysis

Computer security

Hybrid cryptosystem

Telecommunications

IEEE Internet of Things Journal

Edge computing is envisioned to be a powerful platform that provides efficient data storage and computation services in the smart Internet-of-Things (IoT) systems. In this data-intensive architecture, protecting user-side data privacy is one of the most critical concerns to prevent privacy leakage from any other untrusted entities. Aiming to resist this concern, many privacy-preserving data aggregation (PPDA) schemes have been proposed for various cloud-enabled IoT applications. However, due to the resource-constrained nature of the smart IoT devices, the conventional PPDA solutions, in terms of both privacy and performance requirements, are unsuitable in edge computing. To address this challenge, we propose a lightweight and verifiable PPDA scheme, named LVPDA, for the edge-computing-enabled IoT system, where the Paillier homomorphic encryption method and an online/offline signature technique are combined to ensure the privacy preserving and integrity verification during the data aggregation process. A detailed security analysis indicates that LVPDA is existentially unforgeable under the chosen message attack (EU-CMA) and the data integrity can be guaranteed with formal proof under q -strong Diffie-Hellman (q -SDH) assumptions. Compared with other PPDA methods, our scheme can achieve lightweight PPDA in terms of less computational complexity and communication overhead.

LVPDA: A Lightweight and Verifiable Privacy-Preserving Data Aggregation Scheme for Edge-Enabled IoT