本文選題：無線傳感器網(wǎng)絡(luò)　切入點(diǎn)：入侵檢測　出處：《哈爾濱理工大學(xué)》2016年碩士論文

【摘要】：無線傳感器網(wǎng)絡(luò)以其特有的分布性、自組織、自適應(yīng)、微型化、無線連接等特點(diǎn),在工業(yè)生產(chǎn)、環(huán)境監(jiān)測、醫(yī)療、交通等諸多領(lǐng)域被廣泛應(yīng)用,如今伴隨著無線網(wǎng)絡(luò)發(fā)展和智能終端的普及,無線傳感器網(wǎng)絡(luò)越來越被看好,正在印證著“21世紀(jì)最有影響力的技術(shù)之一”這一預(yù)言。同傳統(tǒng)網(wǎng)絡(luò)一樣,無線傳感器網(wǎng)絡(luò)也面臨著各種入侵,且由于無線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)部署環(huán)境多變、能量和計算力有限等特點(diǎn),使得無線傳感器網(wǎng)絡(luò)安全領(lǐng)域存在一些特有的入侵,因而,傳統(tǒng)的入侵檢測系統(tǒng)不能較好的適應(yīng)無線傳感器網(wǎng)絡(luò)。人工免疫系統(tǒng)的自組織、動態(tài)自適應(yīng)、健壯性、分布式、自學(xué)習(xí)這些特點(diǎn)與無線傳感器網(wǎng)絡(luò)恰好吻合,基于人工免疫的無線傳感器網(wǎng)絡(luò)入侵檢測系統(tǒng)也就應(yīng)運(yùn)而生,正是基于免疫的IDS在WSN入侵檢測中存在著先天優(yōu)勢,使其成為新的研究熱點(diǎn)。通過對現(xiàn)有的基于免疫的入侵檢測系統(tǒng)進(jìn)行總結(jié)和分析,針對現(xiàn)有系統(tǒng)廣泛采用二進(jìn)制編碼抗原和抗體導(dǎo)致檢測效果不理想,且不能有效應(yīng)對大規(guī)模入侵,以及親和力計算復(fù)雜等一系列問題,本文提出了一種適應(yīng)于無線傳感器網(wǎng)絡(luò)的RNS-WSN算法,抗原/抗體均采用實(shí)值編碼,同時簡化基因以減少空間占用和運(yùn)算過程,通過曼哈頓距離替代原先的r-連續(xù)位親和力計算方式,并根據(jù)WSN中的入侵特點(diǎn)降低基因的隨機(jī)性,提高了抗體的可用性,通過在NS3平臺上的實(shí)驗驗證,同等能耗下,應(yīng)用RNS-WSN算法的WSN免疫入侵檢測系統(tǒng)能夠獲得比傳統(tǒng)二進(jìn)制編碼更好的檢測結(jié)果,并可以有效應(yīng)對大規(guī)模入侵。針對現(xiàn)有檢測系統(tǒng)中抗體的親和力不足以及針對性差的問題,為體現(xiàn)免疫系統(tǒng)的動態(tài)自適應(yīng)性和進(jìn)化性,受基因混合多層次提取提高多樣性的啟發(fā),本文提出了根據(jù)入侵種類的共性,在面對不同入侵時合理擴(kuò)充對檢測率貢獻(xiàn)度較大的基因所在層上基因的占比來提高親和力,生成針對性強(qiáng)的抗體這一方案,來提升檢測效果。同樣,通過實(shí)驗對該方案進(jìn)行了驗證,結(jié)果表明,根據(jù)入侵特點(diǎn)從網(wǎng)絡(luò)層次混合提取基因,合理配置基因比例,能很好的增強(qiáng)抗原抗體的結(jié)合性,使得抗體面對不同入侵時更有針對性。
[Abstract]:Wireless sensor networks are widely used in many fields such as industrial production, environmental monitoring, medical treatment, transportation and so on, because of their unique characteristics of distribution, self-organization, self-adaptation, miniaturization, wireless connection, etc. With the development of wireless networks and the popularity of intelligent terminals, wireless sensor networks are becoming more and more promising, which is supporting the prediction of "one of the most influential technologies in the 21st century." Wireless sensor networks are also facing various intrusions, and due to the changeable deployment environment, limited energy and computing power of wireless sensor networks, there are some unique intrusion in wireless sensor network security field. The traditional intrusion detection system can not adapt to the wireless sensor network. The artificial immune system is self-organizing, dynamic adaptive, robust and distributed. The intrusion detection system of wireless sensor network based on artificial immune emerges as the times require. It is IDS based on immune that has the innate advantage in WSN intrusion detection. Through the summary and analysis of the existing intrusion detection system based on immunity, the widespread use of binary coding antigen and antibody in the existing system leads to unsatisfactory detection effect. Moreover, it can not effectively deal with a series of problems, such as large-scale intrusion, complex affinity calculation and so on. In this paper, a RNS-WSN algorithm suitable for wireless sensor networks is proposed, in which antigen / antibody is encoded by real value. At the same time, the gene is simplified to reduce the space occupation and operation process, the original r-continuous affinity calculation is replaced by the Manhattan distance, and the randomness of the gene is reduced according to the invading characteristics of WSN, and the availability of antibody is improved. Through the experiment on NS3 platform, under the same energy consumption, the WSN immune intrusion detection system using RNS-WSN algorithm can get better detection results than the traditional binary coding. And can effectively deal with large-scale intrusion. In order to reflect the dynamic adaptability and evolution of the immune system, we can solve the problem of insufficient affinity and poor targeting of antibodies in the existing detection system. Inspired by mixed multilevel extraction of genes to improve diversity, this paper proposes a reasonable expansion of the proportion of genes on the layer where the detection rate is large in the face of different intrusions according to the commonness of the invasive species to improve the affinity. In order to improve the detection effect, the method of producing strong specific antibodies is also verified by experiments. The results show that, according to the characteristics of intrusion, the genes are extracted from the network level, and the proportion of genes is allocated reasonably. It can enhance the binding ability of antigen and antibody, and make the antibody face different invasion.
【學(xué)位授予單位】：哈爾濱理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TP212.9;TN915.08

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