基于移动Sink的WSN安全数据收集方法

苗春雨; 范渊; 李晖; 葛凯强; 张小孟

doi:10.11959/j.issn.2096-109x.2021013

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基于移动Sink的WSN安全数据收集方法

学术论文 | 更新时间：2024-06-03

- 基于移动Sink的WSN安全数据收集方法
- Secure data collection method of WSN based on mobile Sink
- 网络与信息安全学报 2021年7卷第1期页码：121-129
- 作者机构：
  
  1. 杭州安恒信息技术股份有限公司，浙江杭州 310051
  2. 西安电子科技大学网络与信息安全学院，陕西西安 710126
- 作者简介：
  
  [ "苗春雨（1978- ），男，吉林四平人，博士，杭州安恒信息技术股份有限公司高级副总裁，主要研究方向为网络安全体系架构、传感网（物联网）安全。" ]
  [ "范渊（1975- ），男，浙江金华人，杭州安恒信息技术股份有限公司总裁，主要研究方向为应用安全、数据安全。" ]
  [ "李晖（1969- ），男，河南灵宝人，博士，西安电子科技大学教授、博士生导师，主要研究方向为密码与信息安全、信息论与编码理论。" ]
  [ "葛凯强（1992-），男，浙江绍兴人，杭州安恒信息技术股份有限公司工程师，主要研究方向为物联网安全。" ]
  [ "张小孟（1983-），男，浙江温州人，杭州安恒信息技术股份有限公司高级副总裁，主要研究方向为应用安全、Web安全。" ]
- 基金信息：
  
  国家自然科学基金;The National Natural Science Foundation of China(61732022)
- DOI：10.11959/j.issn.2096-109x.2021013
  中图分类号： TP393
- 网络首发：2021-02，
  
  纸质出版：2021-02-15
- 稿件说明：
移动端阅览
苗春雨, 范渊, 李晖, 等. 基于移动Sink的WSN安全数据收集方法[J]. 网络与信息安全学报, 2021,7(1):121-129.

Chunyu MIAO, Yuan FAN, Hui LI, et al. Secure data collection method of WSN based on mobile Sink[J]. Chinese Journal of Network and Information Security, 2021, 7(1): 121-129.
苗春雨, 范渊, 李晖, 等. 基于移动Sink的WSN安全数据收集方法[J]. 网络与信息安全学报, 2021,7(1):121-129. DOI： 10.11959/j.issn.2096-109x.2021013.

Chunyu MIAO, Yuan FAN, Hui LI, et al. Secure data collection method of WSN based on mobile Sink[J]. Chinese Journal of Network and Information Security, 2021, 7(1): 121-129. DOI： 10.11959/j.issn.2096-109x.2021013.

摘要

由于目前基于移动Sink的WSN数据收集方法存在网络攻击检测率不高、内存开销大等问题，导致网络较易受到网络攻击且难以被实际应用。针对该问题，提出一种基于移动Sink的WSN安全数据收集方法，利用能量感知的凸壳算法，识别数据收集点，使用椭圆加密算法（ECC）为网络内的所有节点生成密钥，通过ElGamal算法实现节点身份和消息的认证，使用支持向量机（SVM）识别网络攻击类型。仿真实验结果表明，所提出的安全数据收集方法在攻击检测率、内存开销以及数据包投递率方面都表现出较好的性能。

Abstract

At present

WSN data collection method based on mobile Sink has some problems

such as low detection rate of network attack and large memory cost

which makes the network vulnerable to network attack and difficult to be applied in practice.To solve this problem

a secure data collection WSN method of WSN based on mobile Sink was proposed

which used convex hull algorithm of energy perception to identify data collection points

used elliptic encryption algorithm (ECC) to generate key for all nodes in the network

used ElGamal algorithm to realize node identity and message authentication

and used support vector machine (SVM) to identify network attack types.The simulation results show that the proposed secure data collection method has good performance in attack detection rate

memory overhead and packet delivery rate.

关键词

Keywords

references

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