本文選題：物聯(lián)網(wǎng) + 車聯(lián)網(wǎng)��； 參考：《長(zhǎng)安大學(xué)》2014年碩士論文

【摘要】：隨著車聯(lián)網(wǎng)技術(shù)的應(yīng)用及推廣，車聯(lián)網(wǎng)的安全問題已成為近年來的一個(gè)研究熱點(diǎn)。而信任機(jī)制是解決車聯(lián)網(wǎng)網(wǎng)絡(luò)安全問題的一種有效途徑，信任模型作為信任機(jī)制的核心，通過有效地度量和評(píng)估感知信息，能夠反映車聯(lián)網(wǎng)環(huán)境的動(dòng)態(tài)性和不穩(wěn)定性。同時(shí)，信任模型在處理信任關(guān)系和計(jì)算信譽(yù)度方面具有相當(dāng)?shù)撵`活性，能夠較好地適應(yīng)復(fù)雜多變的車聯(lián)網(wǎng)環(huán)境。 車聯(lián)網(wǎng)的首要目標(biāo)是保證用于采集交通信息的傳感器節(jié)點(diǎn)能夠準(zhǔn)確、及時(shí)提供感知數(shù)據(jù)；其次，車聯(lián)網(wǎng)需要采用數(shù)據(jù)融合技術(shù)處理海量數(shù)據(jù)以提高系統(tǒng)的運(yùn)行效率。因此，為了保障數(shù)據(jù)融合結(jié)果的真實(shí)性與可靠性，本文就車聯(lián)網(wǎng)數(shù)據(jù)融合過程中節(jié)點(diǎn)數(shù)據(jù)被偽造或篡改等安全問題進(jìn)行研究。首先，深入研究了Beth和Josang兩種典型的信任模型，，在分析兩種模型優(yōu)缺點(diǎn)的基礎(chǔ)上，結(jié)合車聯(lián)網(wǎng)的自身特性，對(duì)車聯(lián)網(wǎng)中的直接信任關(guān)系和推薦信任關(guān)系進(jìn)行了描述和度量，提出了一種新的基于節(jié)點(diǎn)信譽(yù)度評(píng)價(jià)的安全數(shù)據(jù)融合模型。其次，采用統(tǒng)計(jì)方法與KL距離理論對(duì)節(jié)點(diǎn)信譽(yù)度進(jìn)行了綜合評(píng)估，考慮信任的時(shí)衰性，在引入時(shí)間衰減因子的前提下，給出了信譽(yù)度的計(jì)算公式和信任關(guān)系表的構(gòu)造方法。針對(duì)信任關(guān)系的實(shí)時(shí)變化，提出了信譽(yù)度的更新算法。最后，根據(jù)節(jié)點(diǎn)的信譽(yù)度，對(duì)節(jié)點(diǎn)進(jìn)行分組融合，并就融合結(jié)果進(jìn)行評(píng)估。該模型在數(shù)據(jù)融合過程中將信譽(yù)度較高的節(jié)點(diǎn)保留，將信譽(yù)度較低的節(jié)點(diǎn)摒棄，從而避免惡意節(jié)點(diǎn)影響融合結(jié)果。 仿真結(jié)果表明，該模型切實(shí)可行，能夠精確地評(píng)估節(jié)點(diǎn)的信譽(yù)度，有效地識(shí)別惡意節(jié)點(diǎn)和惡意推薦行為，從而提高了數(shù)據(jù)融合結(jié)果的準(zhǔn)確性和可靠性。
[Abstract]:With the application and popularization of vehicle networking technology, the safety of vehicle networking has become a research hotspot in recent years. The trust mechanism is an effective way to solve the security problem of the vehicle network. As the core of the trust mechanism, the trust model can reflect the dynamic and instability of the vehicle network environment by effectively measuring and evaluating the perceived information. At the same time, the trust model is flexible in dealing with the trust relationship and calculating the credit degree, and can adapt to the complicated and changeable vehicle networking environment. The primary goal of vehicle networking is to ensure that the sensor nodes used to collect traffic information can accurately and timely provide perceptual data. Secondly, the vehicle networking needs to use data fusion technology to process massive data in order to improve the efficiency of the system. Therefore, in order to ensure the authenticity and reliability of the data fusion results, this paper studies the security problems of node data being forged or tampered in the process of data fusion. Firstly, two typical trust models, Beth and Josang, are studied in depth. Based on the analysis of the advantages and disadvantages of the two models, the direct trust relationship and the recommended trust relationship in the vehicle networking are described and measured in combination with the characteristics of the vehicle networking. A new security data fusion model based on node reputation evaluation is proposed. Secondly, using the statistical method and KL distance theory, the credibility of nodes is evaluated synthetically. Considering the time decay of trust, the calculation formula of reputation and the construction method of trust relation table are given on the premise of introducing time attenuation factor. Aiming at the real-time change of trust relationship, a reputation updating algorithm is proposed. Finally, according to the reputation of the nodes, the nodes are grouped and fused, and the fusion results are evaluated. In the process of data fusion, the nodes with high reputation and those with low reputation are retained in the model, and the malicious nodes are avoided from affecting the fusion results. The simulation results show that the model is feasible, can accurately evaluate the reputation of nodes, and can effectively identify malicious nodes and malicious recommendation behaviors, thus improving the accuracy and reliability of data fusion results.
【學(xué)位授予單位】：長(zhǎng)安大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP391.44;TN929.5;U495

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本文編號(hào)：1849420