Open Access

ARTICLE

Blockchain-Enabled Secure and Privacy-Preserving Data Aggregation for Fog-Based ITS

Siguang Chen^1,2,*, Li Yang^1,2, Yanhang Shi^1,2, Qian Wang¹

1 Jiangsu Key Lab of Broadband Wireless Communication and Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China
2 School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China

* Corresponding Author: Siguang Chen. Email:

Computers, Materials & Continua 2023, 75(2), 3781-3796. https://doi.org/10.32604/cmc.2023.036437

Received 30 September 2022; Accepted 08 February 2023; Issue published 31 March 2023

Abstract

As an essential component of intelligent transportation systems (ITS), electric vehicles (EVs) can store massive amounts of electric power in their batteries and send power back to a charging station (CS) at peak hours to balance the power supply and generate profits. However, when the system collects the corresponding power data, several severe security and privacy issues are encountered. The identity and private injection data may be maliciously intercepted by network attackers and be tampered with to damage the services of ITS and smart grids. Existing approaches requiring high computational overhead render them unsuitable for the resource-constrained Internet of Things (IoT) environment. To address above problems, this paper proposes a blockchain-enabled secure and privacy-preserving data aggregation scheme for fog-based ITS. First, a fog computing and blockchain co-aware aggregation framework of power injection data is designed, which provides strong support for ITS to achieve secure and efficient power injection. Second, Paillier homomorphic encryption, the batch aggregation signature mechanism and a Bloom filter are effectively integrated with efficient aggregation of power injection data with security and privacy guarantees. In addition, the fine-grained homomorphic aggregation is designed for power injection data generated by all EVs, which provides solid data support for accurate power dispatching and supply management in ITS. Experiments show that the total computational cost is significantly reduced in the proposed scheme while providing security and privacy guarantees. The proposed scheme is more suitable for ITS with latency-sensitive applications and is also adapted to deploying devices with limited resources.

---

Keywords

---