Privacy-protecting predictive cache method based on blockchain and machine learning in Internet of vehicles

IF 5.8 2区计算机科学 Q1 TELECOMMUNICATIONS

Vehicular Communications Pub Date : 2024-04-04 DOI:10.1016/j.vehcom.2024.100771

Zihao Shen , Yuanjie Wang , Hui Wang , Peiqian Liu , Kun Liu , Mengke Liu

引用次数: 0

Abstract

To solve the privacy leakage problem faced by Internet of Vehicles (IoV) users when enjoying location-based services (LBS), a privacy-protecting predictive cache method based on blockchain and machine learning (BML-PPPCM) is proposed. First, a Bi-directional Long-Short Term Memory (Bi-LSTM) model is used to predict query requests over a future period based on historical request information. The predicted results are recommended to neighbors and broadcast to requestors. Then, deep Q-learning (DQN) is utilized to determine the optimal cache decision. Finally, a trust mechanism is introduced to calculate trust values, and blockchain is used to store transaction data and trust data, preventing malicious tampering by attackers. The simulation results show that BML-PPPCM has a higher cache hit ratio than other similar schemes and performs well in privacy protection and suppression of malicious and incentive denial of service providers.

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车联网中基于区块链和机器学习的隐私保护预测缓存方法

为了解决车联网（IoV）用户在享受基于位置的服务（LBS）时面临的隐私泄露问题，本文提出了一种基于区块链和机器学习的隐私保护预测缓存方法（BML-PPPCM）。首先，使用双向长短期记忆（Bi-LSTM）模型根据历史请求信息预测未来一段时间内的查询请求。预测结果会推荐给邻居，并广播给请求者。然后，利用深度 Q 学习（DQN）来确定最佳缓存决策。最后，引入信任机制计算信任值，并使用区块链存储交易数据和信任数据，防止攻击者恶意篡改。仿真结果表明，与其他类似方案相比，BML-PPPCM 具有更高的缓存命中率，在隐私保护和抑制恶意及激励性拒绝服务提供方方面表现出色。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Vehicular Communications Engineering-Electrical and Electronic Engineering

CiteScore

12.70

自引率

10.40%

发文量

审稿时长

62 days

期刊介绍： Vehicular communications is a growing area of communications between vehicles and including roadside communication infrastructure. Advances in wireless communications are making possible sharing of information through real time communications between vehicles and infrastructure. This has led to applications to increase safety of vehicles and communication between passengers and the Internet. Standardization efforts on vehicular communication are also underway to make vehicular transportation safer, greener and easier. The aim of the journal is to publish high quality peer–reviewed papers in the area of vehicular communications. The scope encompasses all types of communications involving vehicles, including vehicle–to–vehicle and vehicle–to–infrastructure. The scope includes (but not limited to) the following topics related to vehicular communications: Vehicle to vehicle and vehicle to infrastructure communications Channel modelling, modulating and coding Congestion Control and scalability issues Protocol design, testing and verification Routing in vehicular networks Security issues and countermeasures Deployment and field testing Reducing energy consumption and enhancing safety of vehicles Wireless in–car networks Data collection and dissemination methods Mobility and handover issues Safety and driver assistance applications UAV Underwater communications Autonomous cooperative driving Social networks Internet of vehicles Standardization of protocols.