基于DRG-PBFT和零知识证明的连接和自动驾驶汽车的安全和保护隐私的身份验证框架
Anjum Mohd Aslam1, Aditya Bhardwaj1, Rajat Chaudhary1
1School of Computer Science Engineering & Technology (SCSET), Bennett University (The Times Group), Greater Noida, 201310, Uttar Pradesh, India.
Accident; analysis and prevention
|July 4, 2025
概括
本研究引入了连接和自动驾驶汽车 (CAV) 的新安全框架,提高共识效率和隐私,使用基于动态声誉分组的PBFT (DRG-PBFT) 和SE-ZK-SNARKS进行安全数据交换.
科学领域:
- 智能运输系统 (ITS) 是一种智能运输系统.
- 网络安全 网络安全
- 区块链技术 区块链技术
背景情况:
- 连接和自动驾驶汽车 (CAV) 在实时数据交换中面临着重大安全和隐私风险.
- 现有的共识机制,如实用拜占庭式故障容忍 (PBFT),与可扩展性,延迟和身份伪造等攻击作斗争.
研究的目的:
- 提出一个新的安全框架,基于动态声誉分组的PBFT (DRG-PBFT) 与模拟可提取的零知识简要非交互式知识论证 (SE-ZK-SNARKS) 集成.
- 为了提高共识效率,减少通信开销,并确保CAV的隐私保护身份认证.
主要方法:
- 开发了一种DRG-PBFT方法,包括基于声誉的动态分组,以改善共识.
- 集成的SE-ZK-SNARKS用于CAV的匿名和保护隐私的身份验证.
- 使用NS-3网络模拟与区块链相结合验证了框架.
主要成果:
- 与SE-ZK-SNARKS一起提出的DRG-PBFT与现有方法相比显示出更高的性能.
- 实现了减少共识延迟,降低通信开销和减少身份验证时间.
- 展示了改进的系统吞吐量和对CAV通信的增强安全性.
结论:
- 该DRG-PBFT和SE-ZK-SNARKS框架有效地解决了CAV中关键的安全和隐私挑战.
- 拟议的解决方案提供了一种可扩展和高效的方法,以确保智能运输系统的实时数据交换.
- 这项研究为推进CAV的安全性和可靠性提供了宝贵的参考.
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