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基于Tangle網(wǎng)絡(luò)的移動(dòng)群智感知數(shù)據(jù)安全交付模型

趙國生 張慧 王健

趙國生, 張慧, 王健. 基于Tangle網(wǎng)絡(luò)的移動(dòng)群智感知數(shù)據(jù)安全交付模型[J]. 電子與信息學(xué)報(bào), 2020, 42(4): 965-971. doi: 10.11999/JEIT190370
引用本文: 趙國生, 張慧, 王健. 基于Tangle網(wǎng)絡(luò)的移動(dòng)群智感知數(shù)據(jù)安全交付模型[J]. 電子與信息學(xué)報(bào), 2020, 42(4): 965-971. doi: 10.11999/JEIT190370
Guosheng ZHAO, Hui ZHANG, Jian WANG. A Mobile Crowdsensing Data Security Delivery Model Based on Tangle Network[J]. Journal of Electronics & Information Technology, 2020, 42(4): 965-971. doi: 10.11999/JEIT190370
Citation: Guosheng ZHAO, Hui ZHANG, Jian WANG. A Mobile Crowdsensing Data Security Delivery Model Based on Tangle Network[J]. Journal of Electronics & Information Technology, 2020, 42(4): 965-971. doi: 10.11999/JEIT190370

基于Tangle網(wǎng)絡(luò)的移動(dòng)群智感知數(shù)據(jù)安全交付模型

doi: 10.11999/JEIT190370
基金項(xiàng)目: 國家自然科學(xué)基金(61202458, 61403109),黑龍江自然科學(xué)基金(F2017021),哈爾濱市科技創(chuàng)新人才研究專項(xiàng)資金(2016RAQXJ036)
詳細(xì)信息
    作者簡介:

    趙國生:男,1977年生,博士,教授,研究方向?yàn)榭缮婕夹g(shù)、認(rèn)知網(wǎng)絡(luò)、可信計(jì)算

    張慧:女,1994年生,碩士生,研究方向?yàn)槿褐歉兄?/p>

    王?。号?979年生,博士,教授,研究方向?yàn)镾DN、可生存技術(shù)、認(rèn)知網(wǎng)絡(luò)、群智感知

    通訊作者:

    張慧 18746424159@163.com

  • 中圖分類號(hào): TP309

A Mobile Crowdsensing Data Security Delivery Model Based on Tangle Network

Funds: The National Natural Science Foundation of China (61202458, 61403109), The Natural Science Foundation of Heilongjiang Province (F2017021), The Harbin Science and Technology Innovation Research Funds (2016RAQXJ036)
  • 摘要:

    針對(duì)現(xiàn)有群智感知平臺(tái)在數(shù)據(jù)和酬金交付過程中存在的安全風(fēng)險(xiǎn)和隱私泄露問題,該文提出一種基于Tangle網(wǎng)絡(luò)的分布式群智感知數(shù)據(jù)安全交付模型。首先,在數(shù)據(jù)感知階段,調(diào)用局部異常因子檢測(cè)算法剔除異常數(shù)據(jù),聚類獲取感知數(shù)據(jù)并確定可信參與者節(jié)點(diǎn)。然后,在交易寫入階段,使用馬爾科夫蒙特卡洛算法選擇交易并驗(yàn)證其合法性,通過注冊(cè)認(rèn)證中心登記完成匿名身份數(shù)據(jù)上傳,并將交易同步寫入分布式賬本。最后,結(jié)合Tangle網(wǎng)絡(luò)的累計(jì)權(quán)重共識(shí)機(jī)制,當(dāng)交易安全性達(dá)到閾值時(shí),任務(wù)發(fā)布者可進(jìn)行數(shù)據(jù)和酬金的安全交付。仿真試驗(yàn)表明,在模型保護(hù)用戶隱私的同時(shí),增強(qiáng)了數(shù)據(jù)和酬金的安全交付能力,相比現(xiàn)有感知平臺(tái)降低了時(shí)間復(fù)雜度和任務(wù)發(fā)布成本。

  • 圖  1  基于Tangle網(wǎng)絡(luò)的感知數(shù)據(jù)交付模型

    圖  2  Tangle網(wǎng)絡(luò)交易結(jié)構(gòu)

    圖  3  交易結(jié)構(gòu)

    圖  4  身份匿名過程

    圖  5  隱私數(shù)據(jù)泄露的概率

    圖  6  時(shí)間復(fù)雜性分析

    圖  7  TNM模型與AMT機(jī)制服務(wù)費(fèi)對(duì)比

    表  1  算法1:基于參與者選擇的LOF算法

     輸入:參與者的位置信息集N, k近鄰參數(shù)
     輸出:前k個(gè)數(shù)據(jù)的LOF
     (1) 計(jì)算任意數(shù)據(jù)點(diǎn)之間的歐式距離${\rm{disk}}(i,j)$;
     (2) 計(jì)算所有數(shù)據(jù)點(diǎn)和其前k個(gè)數(shù)據(jù)點(diǎn)間的距離${\rm{disk}}_k^{}(i)$;
     (3) 計(jì)算所有數(shù)據(jù)點(diǎn)的k距離鄰居${N_K}(i)$; $ {N_K}(i) = \left\{ {\left. {i'} \right|} \right.i' \in N, $
    $ \left.{\rm{dist}}(i,i') \le {\rm{dis}}{{\rm{t}}_k}(i) \right\}$
     (4) 計(jì)算所有數(shù)據(jù)點(diǎn)的局部可達(dá)密度${\rm{lr}}{{\rmq7j3ldu95}_k}(i)$:
      $\begin{array}{*{20}{l} }\quad\quad { {\rm{lr} }{ {\rmq7j3ldu95 }_k}(i) = \frac{ {\left\| {\left. { {N_K}(i)} \right\|} \right.} }{ {\displaystyle\sum\limits_{i' \in {N_k}(i)} { {\rm{reachdis} }{ {\rm{t} }_k}(i' \leftarrow i)} } } }\\\qquad { {\rm{reachdis} }{ {\rm{t} }_k}(i' \leftarrow i) = {\rm{max} }\left. {\left\{ { {\rm{dis} }{ {\rm{t} }_k}(i),{\rm{dist} }(i,i')} \right.} \right\} }\end{array}\;\;\;\;\;\;\;\;\quad\ \ \left( 1 \right)$
     (5) 計(jì)算${\rm{LO}}{{\rm{F}}_K}(i)$
      $\begin{array}{*{20}{l}}\quad\quad\ \ {{\rm{LO}}{{\rm{F}}_K}(i) = \frac{{\displaystyle\sum\limits_{i' \in {N_K}(i)} {\frac{{{\rm{lr}}{{\rmq7j3ldu95}_k}(i')}}{{{\rm{lr}}{{\rmq7j3ldu95}_k}(i)}}} }}{{\left\| {\left. {{N_K}(i)} \right\|} \right.}} }\\\quad\quad \quad = {\displaystyle\sum\limits_{i' \in {N_K}(i)} {{\rm{lr}}{{\rmq7j3ldu95}_k}(i') \cdot \sum\limits_{i' \in {N_K}(i)} {{\rm{reachdis}}{{\rm{t}}_k}(i' \leftarrow i)} } }\;\;\;\;\;\;\;\;\;\;\;\;\left( 2 \right)\end{array}$
     (6) 對(duì)${\rm{LO}}{{\rm{F}}_K}(i)$進(jìn)行排序,剔除LOF高的數(shù)據(jù)。
    下載: 導(dǎo)出CSV

    表  2  算法2:基于MCMC的端點(diǎn)選擇算法

     輸入:馬爾可夫鏈狀態(tài)轉(zhuǎn)移矩陣Q,平穩(wěn)分布$\pi (x)$,最大轉(zhuǎn)移次數(shù)n1,選定時(shí)間間隔[W, 2W]及該間隔下的樣本個(gè)數(shù)n2(此時(shí)的樣本個(gè)數(shù)為
    新到的交易所觀察到的交易數(shù)目)。
     輸出:兩個(gè)最先走到Tip的粒子為新交易將驗(yàn)證的端點(diǎn)。
     for t=0 to n1 + n2–1:
     (1) 初始化馬爾可夫鏈${X_0} = {x_0}$;
     (2) 獨(dú)立的在該選定的間隔中隨機(jī)放入N個(gè)粒子定義為“Walker”;
     (3) 每個(gè)粒子根據(jù)定義的轉(zhuǎn)移概率P隨機(jī)的選出一條路徑,向著Tip的方向進(jìn)行游走。其中轉(zhuǎn)移概率定義為:
     $\qquad{P_{xy} } = \dfrac{ { { {\rm e}^{ - a({H_x} - {H_y})} } } }{ {\displaystyle\sum\limits_{z:x \leftarrow z} { { {\rm e}^{ - a({H_x} - {H_z})} } } } }\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad\qquad \left( 3 \right)$
       其中,$a > 0$,為自定義參數(shù),${H_x}$和${H_y}$為交易x和交易y的累計(jì)權(quán)重,轉(zhuǎn)移后第t個(gè)時(shí)刻的馬爾可夫鏈狀態(tài)為${X_t} = {{{x}}_t}$,下一個(gè)交易可
    能的狀態(tài)為${y_{t + 1}} = {x_t}p(x|{x_t})$,此時(shí)$\pi (x) = ({x_{n1} },{x_{n1 + 1} },···,{x_{n1 + n2 - 1} })$。
    下載: 導(dǎo)出CSV

    表  3  群智感知過程中的隱私泄露點(diǎn)

    隱私泄露過程隱私泄露位置竊取隱私難易程度
    參與者將采集數(shù)據(jù)上傳至TS參與者與TS通信的中間網(wǎng)絡(luò)遭受中間人攻擊
    參與者與其他傳感器交互傳感器設(shè)備
    交易寫入Tangle網(wǎng)絡(luò)Tangle網(wǎng)絡(luò)
    TS調(diào)用LOF算法TS
    TS指定獲勝節(jié)點(diǎn)TS
    PS支付酬金PS
    下載: 導(dǎo)出CSV

    表  4  Tangle網(wǎng)絡(luò)處理數(shù)據(jù)的時(shí)間花銷

    名稱任務(wù)發(fā)布任務(wù)接收交易上傳
    任務(wù)大小(kb)處理時(shí)間(ms)任務(wù)大小(kb)處理時(shí)間(ms)任務(wù)大小(kb)處理時(shí)間(ms)
    Task_501179.59489.401289.694.474.7945245.67
    Task_1002356.45620.432416.157.899.7255245.69
    Task_1503552.86722.713932.7713.7914.0229245.65
    Task_2004841.76905.324825.9811.6321.3921245.67
    Task_2505761.841219.455832.9718.2325.7526478.90
    下載: 導(dǎo)出CSV
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  • 收稿日期:  2019-05-23
  • 修回日期:  2019-09-03
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