【摘要】：隨著經(jīng)濟(jì)和互聯(lián)網(wǎng)技術(shù)的快發(fā)發(fā)展,電子政務(wù)在政府信息化管理改革中應(yīng)運(yùn)而生,伴隨而來(lái)的是電子政務(wù)網(wǎng)的安全性保障。網(wǎng)絡(luò)安全評(píng)估技術(shù)針對(duì)網(wǎng)絡(luò)系統(tǒng)的漏洞檢測(cè),網(wǎng)絡(luò)態(tài)勢(shì)感知,攻擊入侵檢測(cè)等方面具有優(yōu)勢(shì),現(xiàn)有的網(wǎng)絡(luò)安全評(píng)估技術(shù)在處理確定性數(shù)據(jù)時(shí)有較好的評(píng)估效果,針對(duì)不確定性信息態(tài)勢(shì)評(píng)估則不盡人意。信息網(wǎng)絡(luò)系統(tǒng)由于其結(jié)構(gòu)的復(fù)雜性,物理設(shè)備多樣性產(chǎn)生的數(shù)據(jù)量大,數(shù)據(jù)信息密度低,給安全評(píng)估帶來(lái)了困難,一方面安全評(píng)估需要保證準(zhǔn)確性,另一方面安全評(píng)估要有實(shí)時(shí)性,然而,現(xiàn)有的安全評(píng)估方法要么通過(guò)犧牲準(zhǔn)確性達(dá)到高效性的目的,要么降低效率獲得高準(zhǔn)確性。因此,網(wǎng)絡(luò)安全評(píng)估方法中滿足評(píng)估結(jié)果準(zhǔn)確性和實(shí)時(shí)性成為一種挑戰(zhàn)。針對(duì)上述挑戰(zhàn),本文提出了一種基于灰色關(guān)聯(lián)分析與D-S證據(jù)理論的網(wǎng)絡(luò)安全評(píng)方法。首先,由于不同評(píng)估指標(biāo)對(duì)于網(wǎng)絡(luò)態(tài)勢(shì)的影響并不相同,利用層次法來(lái)確定不同評(píng)估指標(biāo)的權(quán)重。其次,考慮到不同指標(biāo)對(duì)不同等級(jí)的隸屬度差別,確定了各評(píng)估指標(biāo)對(duì)評(píng)估等級(jí)的隸屬度函數(shù),定義了放大加權(quán)隸屬度函數(shù)來(lái)降低整體不確定性。再者,D-S證據(jù)理論中基本概率分配是一個(gè)難以確定的問(wèn)題,為了減少人為主觀因素對(duì)基本概率分配的差異性影響,提出利用灰色關(guān)聯(lián)分析法來(lái)解決基本概率分配問(wèn)題,然后通過(guò)D-S證據(jù)理論合成規(guī)則對(duì)各Mass函數(shù)進(jìn)行合成,逐步降低不確定性,評(píng)估結(jié)果根據(jù)置信函數(shù)大小確定。通過(guò)實(shí)驗(yàn)表明,該方法降低了評(píng)估結(jié)果的不確定性,提高了準(zhǔn)確性和效率。網(wǎng)絡(luò)安全態(tài)勢(shì)預(yù)測(cè)是在網(wǎng)絡(luò)安全評(píng)估的基礎(chǔ)上對(duì)未來(lái)網(wǎng)絡(luò)安全態(tài)勢(shì)的估計(jì),對(duì)于網(wǎng)絡(luò)安全態(tài)勢(shì)的把握有指導(dǎo)性作用。網(wǎng)絡(luò)安全態(tài)勢(shì)具有突發(fā)性、波動(dòng)性,因此網(wǎng)絡(luò)安全態(tài)勢(shì)勢(shì)預(yù)測(cè)方法要有良好的處理非線性問(wèn)題的能力,對(duì)此,提出了基于GM(1,1)冪模型的網(wǎng)絡(luò)安全態(tài)勢(shì)預(yù)測(cè)方法,GM(1,1)冪模型具有優(yōu)秀的處理非線性問(wèn)題的能力,對(duì)于樣本數(shù)量要求不高,實(shí)用性較好,最后通過(guò)實(shí)驗(yàn)對(duì)比,本文所用的網(wǎng)絡(luò)安全態(tài)勢(shì)預(yù)測(cè)方法較具有較好的預(yù)測(cè)精度和較低的誤差率。
[Abstract]:With the rapid development of economy and Internet technology, e-government emerged as the times require in the government information management reform, accompanied by the security of e-government network. The network security assessment technology has advantages in the aspects of vulnerability detection, network situation awareness, attack intrusion detection and so on. The existing network security assessment technology has a good evaluation effect when dealing with deterministic data. The situation assessment of uncertain information is unsatisfactory. Because of the complexity of its structure, the large amount of data produced by the diversity of physical equipment and the low density of data information, the information network system brings difficulties to the security assessment. On the one hand, the security assessment needs to ensure the accuracy. On the other hand, security assessment should be real-time. However, the existing security assessment methods can achieve high efficiency at the expense of accuracy, or reduce efficiency to achieve high accuracy. Therefore, it is a challenge to satisfy the accuracy and real-time of network security evaluation. In view of the above challenges, this paper presents a network security evaluation method based on grey correlation analysis and D-S evidence theory. Firstly, because the influence of different evaluation indexes on network situation is different, the hierarchical method is used to determine the weight of different evaluation indicators. Secondly, considering the difference of membership degree of different indexes to different grades, the membership function of each evaluation index to evaluation grade is determined, and the enlarged weighted membership function is defined to reduce the overall uncertainty. Furthermore, in D-S evidence theory, the basic probability distribution is a difficult problem. In order to reduce the difference of artificial subjective factors on the basic probability distribution, the grey correlation analysis method is proposed to solve the basic probability distribution problem. Then each Mass function is synthesized by D-S evidence theory synthesis rule, and the uncertainty is reduced step by step. The evaluation results are determined according to the size of the confidence function. Experiments show that this method reduces the uncertainty of the evaluation results and improves the accuracy and efficiency. The prediction of network security situation is based on the evaluation of network security, and it can guide the grasp of network security situation. The network security situation is sudden and fluctuating, so the network security situation forecasting method should have a good ability to deal with nonlinear problems. In this paper, a method of network security situation prediction based on GM (1K1) power model is presented. The power model has excellent ability to deal with nonlinear problems, and it has low requirement for sample size and good practicability. Finally, it is compared by experiments. The network security situation prediction method used in this paper has better prediction accuracy and lower error rate.
【學(xué)位授予單位】：河南工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP393.08

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