不定攻擊中網(wǎng)絡(luò)最弱節(jié)點(diǎn)定位技術(shù)仿真
發(fā)布時(shí)間:2018-06-29 06:43
本文選題:網(wǎng)絡(luò)攻擊 + 節(jié)點(diǎn)定位; 參考:《計(jì)算機(jī)仿真》2013年05期
【摘要】:快速查找攻擊中的最弱節(jié)點(diǎn)能夠更好的保證網(wǎng)絡(luò)安全。傳統(tǒng)的最弱節(jié)點(diǎn)定位方法在應(yīng)用到隨機(jī)攻擊的狀況下時(shí),由于受攻擊節(jié)點(diǎn)隨機(jī)性增大,節(jié)點(diǎn)間的空間關(guān)聯(lián)性迅速下降,攻擊節(jié)點(diǎn)位置不定,因此很難對(duì)特定節(jié)點(diǎn)建立準(zhǔn)確的約束模型,導(dǎo)致節(jié)點(diǎn)定位存在盲點(diǎn),定位準(zhǔn)確性較差。提出了一種改進(jìn)粒子群節(jié)點(diǎn)特征尋優(yōu)算法的不定網(wǎng)絡(luò)攻擊中最弱節(jié)點(diǎn)定位方法。計(jì)算網(wǎng)絡(luò)節(jié)點(diǎn)之間的特征差值,在不定攻擊中網(wǎng)絡(luò)節(jié)點(diǎn)特征提取殘差參數(shù),進(jìn)行極小化處理,通過(guò)設(shè)置粒子群中的每個(gè)粒子代表一個(gè)差異化節(jié)點(diǎn)定位的解,最大程度減小隨機(jī)性帶來(lái)的關(guān)聯(lián)特征弱化問(wèn)題。實(shí)驗(yàn)結(jié)果表明,利用改進(jìn)后的算法進(jìn)行不定攻擊中網(wǎng)絡(luò)最弱節(jié)點(diǎn)定位,能夠有效提高節(jié)點(diǎn)定位的準(zhǔn)確性,從而保證了網(wǎng)絡(luò)的安全性。
[Abstract]:Fast lookup attack in the weakest node can better ensure network security. When the traditional weakest node localization method is applied to the random attack, the spatial correlation between the attacked nodes decreases rapidly, and the location of the attacking node is uncertain because of the increased randomness of the node under attack. Therefore, it is difficult to establish an accurate constraint model for specific nodes, which leads to blind spots and poor positioning accuracy. An improved particle swarm optimization (PSO) algorithm for locating the weakest nodes in uncertain network attacks is proposed. The feature difference between network nodes is calculated, and the residual parameters are extracted from the feature of the network nodes in the uncertain attack. Each particle in the particle swarm represents the solution of the location of a differentiated node by setting the particle swarm. To minimize the randomness of the associated feature weakening problem. The experimental results show that using the improved algorithm to locate the weakest nodes in the indeterminate attack can effectively improve the accuracy of node location and ensure the security of the network.
【作者單位】: 山西大學(xué)商務(wù)學(xué)院;
【基金】:山西省自然科學(xué)基金項(xiàng)目(2010011022-1) 2011年度山西省高?萍奸_(kāi)發(fā)項(xiàng)目(20111134) 2011年度山西省高等學(xué)校教學(xué)改革項(xiàng)目(J2011117) 2011年度山西大學(xué)商務(wù)學(xué)院科研基金項(xiàng)目(JG201102)
【分類號(hào)】:TP393.08
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