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ZigBee網(wǎng)絡(luò)容忍惡意攻擊的安全定位算法

郁濱,  劉子清

郁濱, 劉子清. ZigBee網(wǎng)絡(luò)容忍惡意攻擊的安全定位算法[J]. 電子與信息學(xué)報(bào), 2018, 40(7): 1676-1683. doi: 10.11999/JEIT170962
引用本文: 郁濱, 劉子清. ZigBee網(wǎng)絡(luò)容忍惡意攻擊的安全定位算法[J]. 電子與信息學(xué)報(bào), 2018, 40(7): 1676-1683. doi: 10.11999/JEIT170962
YU Bin, LIU Ziqing. Malicious Attack-resistant Secure Localization Algorithm for ZigBee Network[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1676-1683. doi: 10.11999/JEIT170962
Citation: YU Bin, LIU Ziqing. Malicious Attack-resistant Secure Localization Algorithm for ZigBee Network[J]. Journal of Electronics & Information Technology, 2018, 40(7): 1676-1683. doi: 10.11999/JEIT170962

ZigBee網(wǎng)絡(luò)容忍惡意攻擊的安全定位算法

doi: 10.11999/JEIT170962 cstr: 32379.14.JEIT170962

  • (信息工程大學(xué) 鄭州 450001)

基金項(xiàng)目: 

信息保障技術(shù)重點(diǎn)實(shí)驗(yàn)室開放基金(KJ-15-104)

詳細(xì)信息
    作者簡介:

    郁濱：郁 濱： 男，1964年生，教授，博士生導(dǎo)師，研究方向?yàn)闊o線網(wǎng)絡(luò)安全和視覺密碼. 劉子清： 男，1993年生，碩士生，研究方向?yàn)閆igBee和信息安全技術(shù).

  • 中圖分類號: TP393

Malicious Attack-resistant Secure Localization Algorithm for ZigBee Network

  • YU Bin    LIU Ziqing

Funds: 

The Key Laboratory of Information Assurance Technology Open Fund (KJ-15-104)

  • 摘要: 該文提出一種基于進(jìn)化思想的容忍惡意攻擊安全定位算法(ELAMP)。依據(jù)最大似然估計(jì)概率模型，結(jié)合接收信號強(qiáng)度(RSS)標(biāo)準(zhǔn)差與距離的分布關(guān)系，建立ZigBee網(wǎng)絡(luò)安全定位模型。進(jìn)一步，設(shè)計(jì)進(jìn)化算法對模型進(jìn)行求解，并分析了算法的收斂性和時(shí)間復(fù)雜度。實(shí)驗(yàn)結(jié)果表明，當(dāng)惡意節(jié)點(diǎn)比例不超過50%的情況下，所提算法的定位精度明顯優(yōu)于已有定位算法。
    Abstract: A malicious attack-resistant secure localization algorithm Evolutionary Location Algorithm with the Maximum Probability value (ELAMP) based on evolutionism is proposed. According to the maximum likelihood estimation probability model and the distribution of Received Signal Strength (RSS) standard deviation and the distance, a secure location model of ZigBee network is established. Furthermore, the evolutionary algorithm is designed to solve the model, and the convergence and the time complexity of the algorithm is analyzed. Experimental results show that the proposed algorithm has better positioning accuracy than the existing positioning algorithm when the proportion of malicious nodes is not more than 50%.
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出版歷程
  • 收稿日期:  2017-10-19
  • 修回日期:  2018-03-22
  • 刊出日期:  2018-07-19

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