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基于簡化云與K/N投票的選擇性轉(zhuǎn)發(fā)攻擊檢測方法

尹榮榮,  張文元,  楊綢綢,  李曦達(dá)

尹榮榮, 張文元, 楊綢綢, 李曦達(dá). 基于簡化云與K/N投票的選擇性轉(zhuǎn)發(fā)攻擊檢測方法[J]. 電子與信息學(xué)報(bào), 2020, 42(12): 2841-2848. doi: 10.11999/JEIT190274
引用本文: 尹榮榮, 張文元, 楊綢綢, 李曦達(dá). 基于簡化云與K/N投票的選擇性轉(zhuǎn)發(fā)攻擊檢測方法[J]. 電子與信息學(xué)報(bào), 2020, 42(12): 2841-2848. doi: 10.11999/JEIT190274
Rongrong YIN, Wenyuan ZHANG, Chouchou YANG, Xida LI. A Selective Forwarding Attack Detection Method Based on Simplified Cloud and K/N Voting Model[J]. Journal of Electronics & Information Technology, 2020, 42(12): 2841-2848. doi: 10.11999/JEIT190274
Citation: Rongrong YIN, Wenyuan ZHANG, Chouchou YANG, Xida LI. A Selective Forwarding Attack Detection Method Based on Simplified Cloud and K/N Voting Model[J]. Journal of Electronics & Information Technology, 2020, 42(12): 2841-2848. doi: 10.11999/JEIT190274

基于簡化云與K/N投票的選擇性轉(zhuǎn)發(fā)攻擊檢測方法

doi: 10.11999/JEIT190274
  • 1.

    燕山大學(xué)信息科學(xué)與工程學(xué)院 秦皇島 066004

  • 2.

    燕山大學(xué)河北省特種光纖與光纖傳感重點(diǎn)實(shí)驗(yàn)室 秦皇島 066004

基金項(xiàng)目: 國家自然科學(xué)基金(61802333)，國家留學(xué)基金(201808130258)，河北省高等學(xué)?？茖W(xué)技術(shù)研究項(xiàng)目(QN2018029)
詳細(xì)信息
    作者簡介:

    尹榮榮：女，1985年生，副教授，研究方向?yàn)闊o線傳感器網(wǎng)絡(luò)、網(wǎng)絡(luò)安全

    張文元：男，1991年生，碩士生，研究方向?yàn)闊o線傳感器網(wǎng)絡(luò)攻擊檢測

    楊綢綢：女，1974年生，副研究員，研究方向?yàn)闊o線傳感器網(wǎng)絡(luò)攻擊防御

    李曦達(dá)：女，1977年生，副教授，研究方向?yàn)闊o線傳感器網(wǎng)絡(luò)資源優(yōu)化

    通訊作者:

    尹榮榮　yrr@ysu.edu.cn

  • 中圖分類號: TN915.08; TP393

A Selective Forwarding Attack Detection Method Based on Simplified Cloud and K/N Voting Model

  • 1.

    School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China

  • 2.

    Key Laboratory for Special Fiber and Fiber Sensor of Hebei Province, Yanshan University, Qinhuangdao 066004, China

Funds: The National Natural Science Foundation of China (61802333), The State Scholarship Fund of China (201808130258), The Science and Technology Research Project of Colleges and Universities in Hebei Province (QN2018029)
  • 摘要:

    針對無線傳感器網(wǎng)絡(luò)中惡意節(jié)點(diǎn)產(chǎn)生的選擇性轉(zhuǎn)發(fā)攻擊行為，該文提出一種有效的攻擊檢測方法。該方法將簡化云模型引入信任評估中，結(jié)合改進(jìn)的K/N投票算法確定目標(biāo)節(jié)點(diǎn)的信任值，將目標(biāo)節(jié)點(diǎn)信任值與信任閾值比較，進(jìn)行選擇性轉(zhuǎn)發(fā)攻擊節(jié)點(diǎn)的判定。仿真結(jié)果表明，當(dāng)信任閾值為0.8時(shí)，經(jīng)過5個(gè)時(shí)間段后，該方法能夠有效地檢測出網(wǎng)絡(luò)中的選擇性轉(zhuǎn)發(fā)攻擊節(jié)點(diǎn)，具有較高的檢測率和較低的誤檢率。

    Abstract:

    For the selective forwarding attack behavior generated by malicious nodes in wireless sensor networks, an efficient detection method is proposed. The simplified cloud model is introduced into the trust evaluation model, and the improved K/N voting algorithm is used to obtain the trust value of the target node. Then, the trust value of the target node is compared with the trust threshold to identify the attack node. The simulation results show that when the trust threshold is 0.8 and after 5 time periods, the proposed method can effectively detect the selective forwarding attack nodes, and it has high detection rate and low fault rate.

    • HTML全文

  • 圖  1  基于信任評估模型的選擇性轉(zhuǎn)發(fā)攻擊檢測方法流程圖

    圖  2  信任閾值對檢測率和誤檢率的影響

    圖  3  時(shí)間段對檢測率和誤檢率的影響

    圖  4  惡意節(jié)點(diǎn)比例對節(jié)點(diǎn)信任值的影響

    圖  5  檢測結(jié)果對比圖

    圖  6  惡意節(jié)點(diǎn)比例對檢測率和誤檢率的影響

    表  1  仿真參數(shù)

    參數(shù)值
    時(shí)間段t1000 s
    直接信任值權(quán)重α0.6
    云滴個(gè)數(shù)w100
    包的大小s64 bit
    包傳輸速率v640 bit/s
    下載: 導(dǎo)出CSV
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出版歷程
  • 收稿日期:  2019-04-22
  • 修回日期:  2020-05-28
  • 網(wǎng)絡(luò)出版日期:  2020-11-13
  • 刊出日期:  2020-12-08

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