本文選題：風(fēng)險數(shù)據(jù) + 挖掘��； 參考：《科技通報》2016年05期

【摘要】：在對云計算網(wǎng)絡(luò)漏洞進(jìn)行檢測的過程中,涉及的數(shù)據(jù)量巨大,傳統(tǒng)方法依據(jù)先驗知識建立云計算網(wǎng)絡(luò)漏洞庫,通過和漏洞庫的匹配實現(xiàn)漏洞檢測,實現(xiàn)過程非常復(fù)雜,且建立的漏洞庫也存在局限性,檢測精度低,因此,提出一種基于風(fēng)險數(shù)據(jù)挖掘追蹤的云計算網(wǎng)絡(luò)漏洞檢測技術(shù)。將特征相關(guān)性看作是計算數(shù)據(jù)差異的依據(jù)對風(fēng)險數(shù)據(jù)進(jìn)行初聚類,將和風(fēng)險數(shù)據(jù)有較大差異的正常數(shù)據(jù)剔除,完成初步的處理。引入模糊關(guān)聯(lián)規(guī)則,依據(jù)風(fēng)險數(shù)據(jù)屬性關(guān)聯(lián)規(guī)則,對經(jīng)初聚類處理后的風(fēng)險數(shù)據(jù)進(jìn)行挖掘追蹤,構(gòu)成云計算網(wǎng)絡(luò)漏洞數(shù)據(jù)庫,通過隸屬度分布函數(shù)對漏洞數(shù)據(jù)庫的連續(xù)屬性進(jìn)行模糊處理,依據(jù)模糊關(guān)聯(lián)規(guī)則挖掘構(gòu)建云計算網(wǎng)絡(luò)存在漏洞狀態(tài)時的關(guān)聯(lián)規(guī)則集,用相似度對云計算網(wǎng)絡(luò)當(dāng)前狀態(tài)和存在漏洞狀態(tài)的背離程度進(jìn)行描述,實現(xiàn)云計算網(wǎng)絡(luò)的漏洞檢測。仿真實驗結(jié)果表明,所提方法具有很高的檢測精度和檢測效率。
[Abstract]:In the process of detecting cloud computing network vulnerabilities, the amount of data involved is huge. The traditional method establishes cloud computing network vulnerability library based on prior knowledge, and realizes vulnerability detection by matching vulnerability library, which is very complicated. The vulnerability library also has limitations and low detection accuracy. Therefore, a cloud computing network vulnerability detection technology based on risk data mining tracing is proposed. The feature correlation is regarded as the basis of calculating the difference of data. The risk data is first clustered, and the normal data which is different from the risk data is eliminated, and the preliminary processing is completed. The fuzzy association rule is introduced to mine and trace the risk data after initial clustering according to the risk data attribute association rules, which constitutes the cloud computing network vulnerability database. The continuous attributes of vulnerability database are fuzzy processed by membership degree distribution function, and the association rules set of cloud computing network is constructed according to the mining of fuzzy association rules. This paper describes the degree of deviation between the current state and the existing state of cloud computing network by similarity, and realizes the vulnerability detection of cloud computing network. The simulation results show that the proposed method has high detection accuracy and efficiency.
【作者單位】： 順德職業(yè)技術(shù)學(xué)院電子與信息工程學(xué)院;
【基金】：國家自然科學(xué)基金(編號:41072247)
【分類號】：TP393.08

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 ;漏洞檢測代表產(chǎn)品[J];每周電腦報;2003年46期

2 楊闊朝,蔣凡;模擬攻擊測試方式的漏洞檢測系統(tǒng)的設(shè)計與實現(xiàn)[J];計算機應(yīng)用;2005年07期

3 龍銀香;一種新的漏洞檢測系統(tǒng)方案[J];微計算機信息;2005年05期

4 賈永杰,王恩堂;一種新的漏洞檢測系統(tǒng)方案[J];中國科技信息;2005年09期

5 劉完芳;;基于網(wǎng)絡(luò)的漏洞檢測系統(tǒng)的設(shè)計[J];湘潭師范學(xué)院學(xué)報(自然科學(xué)版);2006年03期

6 金怡;蔡勉;王亞軍;;基于中間件的漏洞檢測系統(tǒng)設(shè)計[J];信息安全與通信保密;2007年04期

7 花青;高嶺;張林;;分布式漏洞檢測系統(tǒng)的設(shè)計與實現(xiàn)[J];東南大學(xué)學(xué)報(自然科學(xué)版);2008年S1期

8 張林;高嶺;湯聲潮;楊e，

本文編號：1872289