發(fā)布時(shí)間：2018-05-03 19:33

  本文選題：對等網(wǎng)絡(luò) + 模糊綜合評(píng)判�。� 參考：《江西理工大學(xué)》2014年碩士論文

【摘要】：網(wǎng)絡(luò)的規(guī)模呈幾何級(jí)數(shù)增長，，網(wǎng)絡(luò)中的各種應(yīng)用也越來越普及，在人們生活中有著不可或缺的地位。與此同時(shí)，由于可信網(wǎng)絡(luò)的自治性、動(dòng)態(tài)性、匿名性，網(wǎng)絡(luò)中的惡意節(jié)點(diǎn)的攻擊行為對網(wǎng)絡(luò)的穩(wěn)定性和可用性造成了很大破壞，這些不安全因素也制約了各種網(wǎng)絡(luò)應(yīng)用的發(fā)展推廣。 信任模型的出現(xiàn)給上述問題的解決提供了新的途徑。通過對國內(nèi)外信任機(jī)制相關(guān)文獻(xiàn)進(jìn)行歸納研究，發(fā)現(xiàn)目前的信任模型大多注重信任計(jì)算值的準(zhǔn)確性，往往忽視了信任本身的模糊性，本文針對這一問題，在綜合國內(nèi)外相關(guān)研究的基礎(chǔ)上，對基于模糊理論的推薦信任模型進(jìn)行研究，研究的主要內(nèi)容包括： （1）P2P網(wǎng)絡(luò)下基于模糊評(píng)判的推薦信任模型。出于提高P2P系統(tǒng)中交易安全性以及提高信任度量準(zhǔn)確性的目的，提出一種基于模糊綜合評(píng)判的推薦信任模型。為了充分體現(xiàn)節(jié)點(diǎn)間信任關(guān)系的模糊性、動(dòng)態(tài)性，采用二層模糊綜合評(píng)判方法來計(jì)算直接信任值，為了降低了人為賦值的誤差，將交易金額和交易時(shí)間作為二層評(píng)判的權(quán)重。在推薦信任計(jì)算中引入節(jié)點(diǎn)交易密度函數(shù)和推薦共謀檢測方法來計(jì)算推薦節(jié)點(diǎn)的推薦可信度。通過仿真實(shí)驗(yàn)驗(yàn)證了該模型可以有效抵御共謀推薦且對惡意節(jié)點(diǎn)有較高的檢測率。 （2）基于用戶行為的模糊理論信任研究。本文以復(fù)雜網(wǎng)絡(luò)環(huán)境為研究背景，運(yùn)用模糊綜合評(píng)判理論，分析研究了針對基于用戶行為的聲譽(yù)評(píng)估策略，在計(jì)算直接信任值的時(shí)候引入時(shí)間段的概念，對不同時(shí)間段的交易給予不同的權(quán)重處理，使得信任的累積具有實(shí)時(shí)性和動(dòng)態(tài)性；在計(jì)算推薦信任值時(shí)加入“震蕩因子”來抵抗震蕩攻擊，提高了信任機(jī)制的健壯性；對如何選擇推薦路徑進(jìn)行探討，給出了較為合理的推薦方法。最后進(jìn)行系統(tǒng)仿真實(shí)驗(yàn)，通過在不同惡意節(jié)點(diǎn)攻擊的情況下與Beth模型的相關(guān)對比驗(yàn)證了本模型的有效性和可用性。
[Abstract]:The scale of network is increasing in geometric series, and the application of network is becoming more and more popular, which plays an indispensable role in people's life. At the same time, because of the autonomy, dynamic and anonymity of trusted network, the attack behavior of malicious nodes in the network has caused great damage to the stability and availability of the network. These insecurity factors also restrict the development and promotion of various network applications. The emergence of trust model provides a new way to solve the above problems. Through the research on the related literatures of trust mechanism at home and abroad, it is found that most of the current trust models pay attention to the accuracy of trust calculation, and often ignore the fuzziness of trust itself. This paper aims at this problem. The recommendation trust model based on fuzzy theory is studied on the basis of synthesizing relevant research at home and abroad. The main contents of the research include: Recommendation trust model based on fuzzy judgment in P2P network. In order to improve the transaction security and the accuracy of trust in P2P system, a recommendation trust model based on fuzzy comprehensive evaluation is proposed. In order to fully reflect the fuzziness and dynamics of the trust relationship between nodes, the two-layer fuzzy comprehensive evaluation method is used to calculate the direct trust value. In order to reduce the error of artificial assignment, the transaction amount and transaction time are taken as the weight of the two-layer evaluation. The node transaction density function and the recommendation collusion detection method are introduced in the recommendation trust calculation to calculate the recommendation credibility of the recommendation node. The simulation results show that the model can resist collusion recommendation effectively and has a high detection rate for malicious nodes. Research on fuzzy theory trust based on user behavior. Based on the complex network environment and the fuzzy comprehensive evaluation theory, this paper analyzes and studies the reputation evaluation strategy based on user behavior, and introduces the concept of time period when calculating the direct trust value. Giving different weights to transactions in different time periods, making the accumulation of trust real-time and dynamic, adding "shock factor" to resist shock attack in the calculation of recommended trust value, improving the robustness of trust mechanism; How to choose the recommended path is discussed, and a more reasonable recommendation method is given. Finally, the system simulation experiments are carried out to verify the effectiveness and availability of the model by comparing it with the Beth model in the case of different malicious node attacks.
【學(xué)位授予單位】：江西理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.08

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