摘要
针对配电物联网中海量数据易受网络攻击的问题,提出一种基于区块链的配电物联网数据安全防护方法。首先,构建一种协作式安全防护架构,通过自适应流量监测设计异常流量识别机制。其次,采用改进实用拜占庭共识(PBFT)算法建立信任机制,实现配电云主站与每个配电边缘代理装置攻击检测模型共享。然后,基于区块链智能合约实现攻击检测模型动态更新,采用深度强化学习训练各攻击检测模型并进行融合,得到攻击检测融合模型。最后,基于Mininet搭建仿真平台并对所提方法进行实验论证,结果表明,所提攻击检测模型综合性能优于集中式和分布式模型。
Aiming at the problem that massive data in distribution Internet of Things is vulnerable to network attack,a data security protection method of distribution Internet of Things based on blockchain is proposed.Firstly,a collaborative security protection architecture is constructed,and the abnormal traffic identification mechanism is designed through adaptive traffic monitoring.Secondly,the improved practical Byzantine fault tolerance(PBFT)is used to establish a trust mechanism to share the attack detection model between the distribution cloud master station and each distribution edge agent.Then,based on the blockchain smart contract,the attack detection model is dynamically updated,and the deep reinforcement learning is used to train and fuse each attack detection model to obtain the attack detection fusion model.Finally,a simulation platform based on Mininet is built to demonstrate the proposed method.The results show that the comprehensive performance of the proposed attack detection model is better than that of centralized and distributed models.
作者
王海
曾飞
杨雄
WANG Hai;ZENG Fei;YANG Xiong(State Grid Jiangsu Electric Power Co.,Ltd.Research Institute,Nanjing 211103,China)
出处
《电力工程技术》
北大核心
2021年第5期47-53,共7页
Electric Power Engineering Technology
基金
国家重点研发计划资助项目(2018YFB0904700)。
关键词
区块链
配电物联网
数据安全防护
实用拜占庭共识(PBFT)
深度强化学习
攻击检测
blockchain
distribution Internet of Things
data security protection
practical Byzantine fault tolerance(PBFT)
deep reinforcement learning
attack detection
