本文選題：蠕蟲(chóng)傳播模型 + 雙時(shí)延　； 參考：《東北大學(xué)》2014年碩士論文

【摘要】：隨著互聯(lián)網(wǎng)技術(shù)的迅猛發(fā)展,網(wǎng)絡(luò)技術(shù)的應(yīng)用已經(jīng)進(jìn)入人們?nèi)粘Ｉ畹母鱾�(gè)角落。在給人們生活帶來(lái)便利的同時(shí),也為蠕蟲(chóng)的大肆傳播創(chuàng)造了條件。建立蠕蟲(chóng)傳播模型是我們研究蠕蟲(chóng)傳播的重要手段之一。然而蠕蟲(chóng)的真實(shí)傳播是異常復(fù)雜的,如人們清殺蠕蟲(chóng)的操作、機(jī)器的重裝系統(tǒng)、蠕蟲(chóng)感染的潛伏行為都會(huì)給蠕蟲(chóng)的傳播帶來(lái)多種時(shí)間延遲。這就使得傳統(tǒng)的單時(shí)延蠕蟲(chóng)傳播模型不能夠真實(shí)的模擬蠕蟲(chóng)在現(xiàn)實(shí)世界中的傳播情況,因此如何準(zhǔn)確地預(yù)測(cè)蠕蟲(chóng)在網(wǎng)絡(luò)中真實(shí)的傳播已成為時(shí)下重要的課題。本文在傳染病學(xué)和非線性動(dòng)力學(xué)的研究成果基礎(chǔ)上,首先對(duì)由于清殺操作所導(dǎo)致的時(shí)延在蠕蟲(chóng)傳播中產(chǎn)生的影響進(jìn)行了分析并且建模,提出了具有免疫時(shí)延的SIDV蠕蟲(chóng)傳播模型,然后對(duì)此模型進(jìn)行了穩(wěn)定性分析和數(shù)值模擬。為了更加真實(shí)地預(yù)測(cè)和遏制蠕蟲(chóng)的傳播,本文在SIDV模型的基礎(chǔ)上,提出了更加完整的抑制策略,即采用入侵檢測(cè)系統(tǒng)的隔離策略。由于其中的濫用檢測(cè)系統(tǒng)通過(guò)設(shè)置時(shí)間窗口來(lái)提高檢測(cè)率,而時(shí)間窗口會(huì)導(dǎo)致系統(tǒng)產(chǎn)生時(shí)延因素。因此,本文提出了蠕蟲(chóng)雙時(shí)延傳播模型,并且對(duì)蠕蟲(chóng)雙時(shí)延傳播模型進(jìn)行穩(wěn)定性分析和Hopf分岔分析。理論推導(dǎo)表明,蠕蟲(chóng)雙時(shí)延模型對(duì)于兩個(gè)時(shí)延分別存在一個(gè)時(shí)延臨界值,當(dāng)兩個(gè)時(shí)延均小于它們的臨界值時(shí),系統(tǒng)是穩(wěn)定且易于控制的,而且在使用隔離策略之后,感染主機(jī)的最終數(shù)量也有明顯的下降；而當(dāng)其中一個(gè)時(shí)延超出臨界值或者兩個(gè)時(shí)延同時(shí)超出臨界值時(shí),系統(tǒng)就會(huì)出現(xiàn)Hopf分岔,從而致使蠕蟲(chóng)的傳播無(wú)法控制,并且抑制策略失效。這表明,人們應(yīng)該在主機(jī)感染蠕蟲(chóng)后及時(shí)的清殺蠕蟲(chóng)并且時(shí)間窗口的尺寸應(yīng)該控制小于隔離時(shí)延的閾值,從而保證整個(gè)傳播系統(tǒng)的穩(wěn)定性。為了驗(yàn)證結(jié)論,本文進(jìn)行了數(shù)值模擬與仿真實(shí)驗(yàn),實(shí)驗(yàn)結(jié)果證明了本文理論分析的正確性。
[Abstract]:With the rapid development of Internet technology, the application of network technology has entered every corner of people's daily life. While bringing convenience to people's lives, it also creates conditions for the rampant spread of worms. Establishing worm propagation model is one of the important methods to study worm propagation. However, the real propagation of worms is extremely complicated. For example, the operation of killing worms, the reloading of machines, and the latent behavior of worm infection will bring a variety of time delays to the propagation of worms. This makes the traditional single-delay worm propagation model can not really simulate the worm propagation in the real world, so how to accurately predict the real worm propagation in the network has become an important issue. Based on the research results of infectious diseases and nonlinear dynamics, this paper first analyzes the effects of the delay caused by the killing operation on the propagation of worms, and proposes a SIDV worm propagation model with immune delay. Then the stability analysis and numerical simulation of the model are carried out. In order to predict and control worm propagation more realistically, this paper proposes a more complete suppression strategy based on SIDV model, that is, the isolation strategy of intrusion detection system (IDS). Because the abuse detection system can improve the detection rate by setting the time window, the time window will lead to the delay factor of the system. Therefore, a worm double delay propagation model is proposed, and the stability analysis and Hopf bifurcation analysis of the worm double delay propagation model are carried out. The theoretical derivation shows that the worm dual delay model has a delay critical value for each of the two delays. When both time delay is less than their critical value, the system is stable and easy to control, and after using the isolation strategy, the system is stable and easy to control. The final number of infected hosts is also significantly reduced; when one of the delays exceeds the threshold or when both delays exceed the threshold, Hopf bifurcation occurs in the system, causing the worm to spread out of control. And the inhibition strategy is invalid. This indicates that people should kill the worm in time after the host is infected and the size of the time window should be controlled less than the threshold of the isolation delay to ensure the stability of the whole transmission system. In order to verify the conclusion, numerical simulation and simulation experiments are carried out, and the experimental results prove the correctness of the theoretical analysis.
【學(xué)位授予單位】：東北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.08

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 ;Proactive worm propagation modeling and analysis in unstructured peer-to-peer networks[J];Journal of Zhejiang University-Science C(Computer & Electronics);2010年02期

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本文編號(hào)：2049458