基于安全等級(jí)模型的社交網(wǎng)絡(luò)蠕蟲(chóng)安全檢測(cè)方法研究
發(fā)布時(shí)間:2018-10-12 09:04
【摘要】:近幾年,網(wǎng)絡(luò)蠕蟲(chóng)已經(jīng)成為計(jì)算機(jī)網(wǎng)絡(luò)安全中的重大問(wèn)題。網(wǎng)絡(luò)蠕蟲(chóng)是一段獨(dú)立的惡意代碼,具備自我復(fù)制和傳播的能力。傳統(tǒng)的網(wǎng)絡(luò)蠕蟲(chóng)編寫成本雖然簡(jiǎn)單,但是其自我繁殖、惡意發(fā)包能力強(qiáng),擴(kuò)散速度極快,能夠在短時(shí)間內(nèi)大量覆蓋網(wǎng)絡(luò)中主機(jī),耗盡網(wǎng)絡(luò)資源,造成巨大的經(jīng)濟(jì)損失。一旦網(wǎng)絡(luò)蠕蟲(chóng)大量擴(kuò)散造成網(wǎng)絡(luò)癱瘓,恢復(fù)工作同樣需要耗費(fèi)大量的時(shí)間和資源。繼門戶網(wǎng)站、搜索引擎后,社交網(wǎng)絡(luò)成為全球互聯(lián)網(wǎng)商業(yè)模式的第三次浪潮,具有巨大的商業(yè)價(jià)值。社交型網(wǎng)絡(luò)蠕蟲(chóng)(以下簡(jiǎn)稱“社交網(wǎng)絡(luò)蠕蟲(chóng)”)是利用社會(huì)工程學(xué)以各種方式誘惑用戶點(diǎn)擊進(jìn)行傳播的一類蠕蟲(chóng),在保留了傳統(tǒng)計(jì)算機(jī)網(wǎng)絡(luò)的惡意特性基礎(chǔ)上,社交網(wǎng)絡(luò)蠕蟲(chóng)通過(guò)結(jié)合社會(huì)工程學(xué)技術(shù),具備更強(qiáng)的隱蔽性、誘惑性、更長(zhǎng)的生存周期,更加復(fù)雜的傳播方式。針對(duì)社交網(wǎng)絡(luò)蠕蟲(chóng)的安全問(wèn)題研究,近幾年來(lái)逐漸得到更多研究人員的關(guān)注。 在這樣的情況下,本文對(duì)當(dāng)前國(guó)內(nèi)、國(guó)際針對(duì)傳統(tǒng)網(wǎng)絡(luò)蠕蟲(chóng)、社交網(wǎng)絡(luò)蠕蟲(chóng)及其相關(guān)問(wèn)題的研究現(xiàn)狀進(jìn)行總結(jié)。說(shuō)明了社交網(wǎng)絡(luò)蠕蟲(chóng)‘傳播模型在社交網(wǎng)絡(luò)安全問(wèn)題中的重要性,比較并分析了傳染病傳播模型、高級(jí)傳播模型的特性,最終提出了一種基于社交網(wǎng)絡(luò)的蠕蟲(chóng)傳播模型。 闡釋了社交網(wǎng)絡(luò)蠕蟲(chóng)檢測(cè)技術(shù)的重要性;提出了幾種檢測(cè)技術(shù)的‘分類,從而深入分析各種檢測(cè)技術(shù)的特性和適用情況;提出了社交網(wǎng)絡(luò)蠕蟲(chóng)的性能指標(biāo),從而更好地評(píng)價(jià)社交網(wǎng)絡(luò)蠕蟲(chóng)檢測(cè)技術(shù);提出了一種基于安全等級(jí)模型的社交網(wǎng)絡(luò)蠕蟲(chóng)檢測(cè)技術(shù),并對(duì)檢測(cè)的方法和各個(gè)模塊設(shè)計(jì)進(jìn)行說(shuō)明。
[Abstract]:In recent years, network worms have become a major problem in computer network security. A web worm is a separate piece of malicious code capable of self-replication and propagation. Although the cost of traditional network worm writing is simple, its self-propagation, malicious outsourcing ability, rapid diffusion speed, can cover a large number of hosts in the network in a short time, deplete the network resources, and cause huge economic losses. Once a large number of network worms spread resulting in network paralysis, recovery will also take a lot of time and resources. After portal, search engine, social network has become the third wave of the global Internet business model, which has great commercial value. Social network worm (hereafter referred to as "social network worm") is a kind of worm that uses social engineering to tempt users to click and spread in various ways, on the basis of retaining the malicious character of traditional computer network. By combining social engineering technology, social network worms have more concealment, seduction, longer life cycle and more complex modes of transmission. In recent years, more and more researchers have paid attention to the security of social network worms. In this case, this paper summarizes the current domestic and international research on traditional network worms, social network worms and their related problems. This paper explains the importance of the social network worm 'propagation model in the social network security, compares and analyzes the characteristics of the infectious disease transmission model and the advanced transmission model, and finally puts forward a worm propagation model based on the social network. In this paper, the importance of social network worm detection technology is explained, the 'classification of several detection techniques is put forward, and the characteristics and application of various detection techniques are analyzed in depth, and the performance index of social network worm is put forward. In order to better evaluate the social network worm detection technology, a social network worm detection technology based on security level model is proposed, and the detection method and the design of each module are described.
【學(xué)位授予單位】:北京郵電大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2013
【分類號(hào)】:TP393.08
本文編號(hào):2265554
[Abstract]:In recent years, network worms have become a major problem in computer network security. A web worm is a separate piece of malicious code capable of self-replication and propagation. Although the cost of traditional network worm writing is simple, its self-propagation, malicious outsourcing ability, rapid diffusion speed, can cover a large number of hosts in the network in a short time, deplete the network resources, and cause huge economic losses. Once a large number of network worms spread resulting in network paralysis, recovery will also take a lot of time and resources. After portal, search engine, social network has become the third wave of the global Internet business model, which has great commercial value. Social network worm (hereafter referred to as "social network worm") is a kind of worm that uses social engineering to tempt users to click and spread in various ways, on the basis of retaining the malicious character of traditional computer network. By combining social engineering technology, social network worms have more concealment, seduction, longer life cycle and more complex modes of transmission. In recent years, more and more researchers have paid attention to the security of social network worms. In this case, this paper summarizes the current domestic and international research on traditional network worms, social network worms and their related problems. This paper explains the importance of the social network worm 'propagation model in the social network security, compares and analyzes the characteristics of the infectious disease transmission model and the advanced transmission model, and finally puts forward a worm propagation model based on the social network. In this paper, the importance of social network worm detection technology is explained, the 'classification of several detection techniques is put forward, and the characteristics and application of various detection techniques are analyzed in depth, and the performance index of social network worm is put forward. In order to better evaluate the social network worm detection technology, a social network worm detection technology based on security level model is proposed, and the detection method and the design of each module are described.
【學(xué)位授予單位】:北京郵電大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2013
【分類號(hào)】:TP393.08
【參考文獻(xiàn)】
相關(guān)期刊論文 前2條
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2 FAHIM A.M;SALEM A.M;TORKEY F.A;RAMADAN M.A;;An efficient enhanced k-means clustering algorithm[J];Journal of Zhejiang University Science A(Science in Engineering);2006年10期
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