【摘要】：在云計(jì)算環(huán)境下,傳統(tǒng)方法采用終端網(wǎng)絡(luò)監(jiān)測(cè)方法進(jìn)行網(wǎng)絡(luò)安全估計(jì),由于網(wǎng)絡(luò)通信信道終端功率衰減性強(qiáng),導(dǎo)致安全態(tài)勢(shì)估計(jì)精度不高,檢測(cè)性能不好。提出一種基于自適應(yīng)數(shù)據(jù)分類(lèi)和病毒感染隸屬度特征提取的云計(jì)算環(huán)境下網(wǎng)絡(luò)安全估計(jì)及態(tài)勢(shì)預(yù)測(cè)算法。構(gòu)建云計(jì)算環(huán)境下的網(wǎng)絡(luò)安全估計(jì)模型,采用自適應(yīng)數(shù)據(jù)分類(lèi)算法對(duì)網(wǎng)絡(luò)攻擊信息數(shù)據(jù)進(jìn)行聚類(lèi)評(píng)估,提取網(wǎng)絡(luò)攻擊病毒數(shù)據(jù)的感染隸屬度特征,實(shí)現(xiàn)網(wǎng)絡(luò)安全態(tài)勢(shì)預(yù)測(cè)和病毒攻擊檢測(cè)。仿真實(shí)驗(yàn)表明,該算法對(duì)病毒數(shù)據(jù)流預(yù)測(cè)精度較高,實(shí)現(xiàn)不同場(chǎng)景下的網(wǎng)絡(luò)病毒流預(yù)測(cè)和數(shù)據(jù)檢測(cè),提高了云計(jì)算環(huán)境下網(wǎng)絡(luò)抵御病毒攻擊的能力。
[Abstract]:In cloud computing environment, the traditional method of terminal network monitoring is used to estimate network security. Because of the strong power attenuation of network communication channel, the accuracy of security situation estimation is not high and the detection performance is poor. An algorithm for network security estimation and situation prediction in cloud computing environment based on adaptive data classification and virus infection membership feature extraction is proposed. The network security estimation model in cloud computing environment is constructed, and the adaptive data classification algorithm is used to cluster and evaluate the network attack information data, and extract the infection membership characteristics of the network attack virus data. Network security situation prediction and virus attack detection are realized. The simulation results show that the proposed algorithm has high prediction accuracy for virus data flow, and realizes network virus flow prediction and data detection in different scenarios, and improves the ability of network to resist virus attack in cloud computing environment.
【作者單位】： 成都航空職業(yè)技術(shù)學(xué)院計(jì)算機(jī)工程系;
【基金】：四川省自然科學(xué)重點(diǎn)項(xiàng)目:云計(jì)算在信息化建設(shè)中的應(yīng)用研究(15ZA0399)
【分類(lèi)號(hào)】：TP393.08

【參考文獻(xiàn)】

相關(guān)期刊論文 前8條

1 韋勇;連一峰;;基于日志審計(jì)與性能修正算法的網(wǎng)絡(luò)安全態(tài)勢(shì)評(píng)估模型[J];計(jì)算機(jī)學(xué)報(bào);2009年04期

2 王晟;趙壁芳;;基于模糊數(shù)據(jù)挖掘和遺傳算法的網(wǎng)絡(luò)入侵檢測(cè)技術(shù)[J];計(jì)算機(jī)測(cè)量與控制;2012年03期

3 衣曉;鄧露;劉瑜;;基于基站劃分網(wǎng)格的無(wú)線(xiàn)傳感器網(wǎng)絡(luò)分簇算法[J];控制理論與應(yīng)用;2012年02期

4 劉邏;郭立紅;肖輝;王建軍;王改革;;基于參數(shù)動(dòng)態(tài)調(diào)整的動(dòng)態(tài)模糊神經(jīng)網(wǎng)絡(luò)的軟件可靠性增長(zhǎng)模型[J];計(jì)算機(jī)科學(xué);2013年02期

5 劉雷雷;臧洌;邱相存;;基于Kalman算法的網(wǎng)絡(luò)安全態(tài)勢(shì)預(yù)測(cè)[J];計(jì)算機(jī)與數(shù)字工程;2014年01期

6 羅龍;虞紅芳;羅壽西;;基于多拓?fù)渎酚傻臒o(wú)擁塞快速業(yè)務(wù)遷移算法[J];計(jì)算機(jī)應(yīng)用;2015年07期

7 匡桂娟;曾國(guó)蓀;熊煥亮;;關(guān)注用戶(hù)服務(wù)評(píng)價(jià)反饋的云資源再分配方法[J];計(jì)算機(jī)應(yīng)用;2015年07期

8 孫超;楊春曦;范莎;武寧;;能量高效的無(wú)線(xiàn)傳感器網(wǎng)絡(luò)分布式分簇一致性濾波算法[J];信息與控制;2015年03期

【共引文獻(xiàn)】

相關(guān)期刊論文 前10條

1 李寶s，

本文編號(hào)：2411591