应用科学学报 ›› 2019, Vol. 37 ›› Issue (2): 213-223.doi: 10.3969/j.issn.0255-8297.2019.02.006

• 区块链 • 上一篇    下一篇

基于区块链的防护物联网设备DDoS攻击方法

周启惠1, 邓祖强3, 邹萍2, 王秋生3, 李艳东2, 姜海森2   

  1. 1. 中国科学院信息工程研究所网络与系统安全实验室, 北京 100093;
    2. 北京航天智造科技发展有限公司, 北京 100039;
    3. 南瑞集团公司(国家电网电力研究院), 北京 102200
  • 收稿日期:2018-12-15 修回日期:2019-01-15 出版日期:2019-03-31 发布日期:2019-03-31
  • 作者简介:周启惠,助理研究员,研究方向:区块链技术及平台,E-mail:zhouqihui@iie.ac.cn
  • 基金资助:
    国家重点研发计划(No.2018YFB1004000);政府间国际科技创新合作重点专项(No.2017YFE0101100)资助

DDoS Defense Method of IoT Devices Based on Blockchain

HOU Qi-hui1, DENG Zu-qiang3, ZOU Ping2, WANG Qiu-sheng3, LI Yan-dong2, JIANG Hai-sen2   

  1. 1. Laboratory of Network and System Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China;
    2. Beijing Aerospace Smart Manufacturing Technology Development Co., Ltd, Beijing 100039, China;
    3. NARI Group Corporation(State Grid Electric Power Research Institute), Beijing 102200, China
  • Received:2018-12-15 Revised:2019-01-15 Online:2019-03-31 Published:2019-03-31

摘要: 随着物联网设备的普及,利用物联网设备发起的分布式拒绝服务攻击(distributeddenial service,DDoS)愈演愈烈,针对此类问题,提出了一种基于边缘计算和区块链的检测防御架构.在边缘节点依据物联网设备的业务功能特点实现了初步的疑似DDoS异常检测,初步检测结果的共享分析得出DDoS预警,最终对物联网设备发出的DDoS进行过滤.该方案的检测防御分布式部署在攻击源端,可以避免引流及流量清洗造成的高额成本和网络阻塞,并可以在检测到DDoS发生之初在源头进行持续过滤从而阻止攻击流量的上涨.

关键词: 区块链, 边缘计算, 物联网设备, 分布式拒绝服务攻击, 共享分析

Abstract: With the popularity of internet of things (IoT) devices, distributed denial of service (DDoS) attacks initiated by IoT devices have become ferce. To solve such problems, this paper proposes a detection and defense architecture based on edge computing and blockchain. According to the business characteristics of IoT devices, the suspected DDoS anomaly detection is implemented at edge nodes. Then the DDoS warning is obtained by sharing and analyzing the preliminary results with blockchain. Finally, DDoS connection is fltered at edge nodes based on the reward mechanism. The detection and defense is deployed at the source distributely, which can avoid high cost and network congestion caused by trafc extraction and cleaning, and can prevent the increasement of total DDoS trafc by fltering the trafc continuously at the source when DDoS is detected.

Key words: distributed denial of service (DDoS), share & analysis, blockchain, edge computing, IoT devices

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