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基于软件定义安全的配电物联网分组转发异常检测

Packet Forwarding Abnormality Detection in Power IoT Based on Software-Defined Security

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针对配电物联网"云、管、边、端"架构中云平台与边缘设备远程通信中存在的恶意的分组注入、篡改、丢弃与劫持攻击,提出基于软件定义安全的配电物联网分组转发异常检测机制,克服了传统网络通过插入随路径长度以线性尺度增加密码标签的方式实现分组转发检测引入的计算与带宽开销大的缺点.机制结合软件定义架构,通过地址跳变将网络流运行时间分割为随机的时隙,网络节点基于跳变的地址信息转发分组,流边缘入口与出口交换机采样该时隙内的分组并生成流量梗概,控制器基于流量梗概检测分组转发异常;最后,构建仿真网络实现了所提机制,分析与实验表明该开销小于同类机制,引入了不超过11%的转发延迟与低于10%的吞吐率损失,可有效检测物联网云边远程通信分组转发异常.
Malicious packet injection,tampering,dropping and hijacking attacks exist in the remote communication between the cloud platform and the edge devices in the power Internet of Things with the architecture of"Cloud,Network,Edge and Terminal".An abnormality detection mechanism in power Internet of Things based on software-defined security is proposed,which overcomes the draw-backs of computation and bandwidth overhead incurred by inserting cryptographic tags that increase linear-scally as path lengthen in the traditional network.Based on the software-defined architec-ture,a flow running time is split into consecutive random epoch by address hopping.Each switch forwards packets according to the hopping address,the ingress and egress switch samples packets and generates traffic sketch in each epoch,and the controller detect abnormality based on the sketch.The proposed scheme is implemented and evaluated.The analyses and experiments demon-strate that the communication overhead of the proposed mechanism is less than the existing mecha-nisms,with less than 11%of additional forwarding delay and no more than 10%of throughput deg-radation.Therefore,the proposed scheme could effectively detects abnormality.

software-definedpower Internet of Thingstraffic sketchpacket forwardingabnor-mality detection

吴平、孙浩洋、周莉梅、尚宇炜、高飞

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北京云谷科创信息科技有限公司 北京 100036

中国电力科学研究院有限公司 北京 100192

软件定义 配电物联网 流量梗概 分组转发 异常检测

国家电网科学技术基金

5400-202255159A-1-1-ZN

2024

信息工程大学学报
中国人民解放军信息工程大学科研部

信息工程大学学报

影响因子:0.276
ISSN:1671-0673
年,卷(期):2024.25(2)
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