【摘要】：在網(wǎng)絡(luò)安全態(tài)勢(shì)評(píng)估中,各種傳感器報(bào)警數(shù)據(jù)多樣且復(fù)雜,評(píng)估的經(jīng)驗(yàn)知識(shí)和先驗(yàn)概率難以獲取,使得準(zhǔn)確分析和評(píng)估網(wǎng)絡(luò)安全態(tài)勢(shì)十分困難.針對(duì)上述問題,對(duì)安全傳感器采集到的數(shù)據(jù)建立隱馬爾可夫模型,將難以解決的多源異構(gòu)數(shù)據(jù)統(tǒng)一融合問題轉(zhuǎn)化為計(jì)算聯(lián)合概率的問題.利用前向算法特點(diǎn),近似計(jì)算出聯(lián)合概率,避免了直接計(jì)算先驗(yàn)概率的困難,并引入聯(lián)合信息熵來描述網(wǎng)絡(luò)安全態(tài)勢(shì).實(shí)驗(yàn)驗(yàn)證了該方法的有效性,與基于概率的態(tài)勢(shì)評(píng)估方法相比,該方法能更清晰地說明網(wǎng)絡(luò)安全狀態(tài)的穩(wěn)定程度及趨勢(shì).
[Abstract]:In the network security situation assessment, all kinds of sensor alarm data are diverse and complex, and the experience knowledge and prior probability of the evaluation are difficult to obtain, which makes it very difficult to accurately analyze and evaluate the network security situation. In view of the above problems, the hidden Markov model is established for the data collected by the security sensor, and the problem of unified fusion of multi-source and heterogeneous data is transformed into the problem of computing the joint probability. Based on the characteristics of forward algorithm, the joint probability is approximately calculated, which avoids the difficulty of directly calculating the prior probability, and the joint information entropy is introduced to describe the network security situation. Compared with the probability-based situation assessment method, this method can clearly explain the stability and trend of the network security state.
【作者單位】： 河南省計(jì)算機(jī)信息系統(tǒng)安全評(píng)估工程實(shí)驗(yàn)室;中原工學(xué)院計(jì)算機(jī)學(xué)院;信息工程大學(xué);
【基金】：國(guó)家自然聯(lián)合基金項(xiàng)目(U1304606)資助 河南省科技攻關(guān)項(xiàng)目(132102310284)資助 鄭州市科技攻關(guān)項(xiàng)目(2010GYXM421)資助
【分類號(hào)】：TP393.08

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