本文關(guān)鍵詞：車聯(lián)網(wǎng)軌跡數(shù)據(jù)隱私保護(hù)問(wèn)題研究　出處：《河南工業(yè)大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

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【摘要】：隨著車載定位技術(shù)和移動(dòng)自組織網(wǎng)絡(luò)技術(shù)的飛速發(fā)展,車聯(lián)網(wǎng)(VANETs)相關(guān)技術(shù)已引起國(guó)內(nèi)外政府、學(xué)術(shù)界和產(chǎn)業(yè)界的高度重視并成為熱點(diǎn)話題。目前車聯(lián)網(wǎng)與工業(yè)4.0、可穿戴設(shè)備成為當(dāng)前物聯(lián)網(wǎng)領(lǐng)域的三大研究熱點(diǎn)。車聯(lián)網(wǎng)的部署能夠?qū)崿F(xiàn)智能駕駛、交通管理以及車載娛樂(lè)等等。但是機(jī)遇與挑戰(zhàn)并存,在車聯(lián)網(wǎng)飛速發(fā)展的同時(shí)也面臨著數(shù)據(jù)安全、隱私泄露的風(fēng)險(xiǎn)。未來(lái)車聯(lián)網(wǎng)中每輛車上有超過(guò)80個(gè)傳感器,每天向后臺(tái)云服務(wù)器傳輸?shù)臄?shù)據(jù)量可達(dá)到100MB,這些數(shù)據(jù)覆蓋了車輛和用戶的個(gè)人信息、行為模式等敏感信息,攻擊者可以通過(guò)竊聽通信過(guò)程中的廣播消息、分析數(shù)據(jù)、預(yù)測(cè)軌跡、跟蹤車輛從而獲取車輛的敏感數(shù)據(jù)。用戶的個(gè)人隱私甚至人身安全都將受到威脅。因此想要大規(guī)模的部署車聯(lián)網(wǎng),首先要面臨的問(wèn)題就是數(shù)據(jù)的隱私安全問(wèn)題,而對(duì)于車聯(lián)網(wǎng)來(lái)說(shuō),其中最主要的數(shù)據(jù)就是車輛的軌跡數(shù)據(jù)。本文首先通過(guò)對(duì)車聯(lián)網(wǎng)的潛在的軌跡隱私需求進(jìn)行系統(tǒng)的分析。針對(duì)車聯(lián)網(wǎng)不同應(yīng)用場(chǎng)景下的軌跡隱私問(wèn)題進(jìn)行分析,針對(duì)如何保護(hù)車聯(lián)網(wǎng)軌跡隱私數(shù)據(jù)和防止敏感信息泄露進(jìn)行了闡述,分別介紹了目前主流的隱私保護(hù)技術(shù)并通過(guò)分析對(duì)現(xiàn)有的隱私保護(hù)方案進(jìn)行對(duì)比,并說(shuō)明其存在的問(wèn)題。針對(duì)車聯(lián)網(wǎng)軌跡隱私問(wèn)題,分別在車聯(lián)網(wǎng)網(wǎng)內(nèi)數(shù)據(jù)傳遞與數(shù)據(jù)發(fā)布過(guò)程兩種應(yīng)用場(chǎng)景,引入差分隱私思想研究車載網(wǎng)絡(luò)軌跡數(shù)據(jù)發(fā)布過(guò)程中的隱私保護(hù)問(wèn)題,通過(guò)理論分析、建模和實(shí)驗(yàn),探索適合車聯(lián)網(wǎng)軌跡隱私保護(hù)機(jī)制。最后分別從數(shù)據(jù)質(zhì)量和軌跡數(shù)據(jù)可用性兩個(gè)角度,對(duì)本文提出的隱私保護(hù)算法進(jìn)行性能測(cè)評(píng)并與現(xiàn)有的隱私保護(hù)方案進(jìn)行對(duì)比。實(shí)驗(yàn)結(jié)果顯示差分隱私在車聯(lián)網(wǎng)網(wǎng)內(nèi)軌跡隱私保護(hù)方面不僅有良好的隱私保護(hù)效果而且能夠有效的緩解通信壓力,對(duì)于面向位置服務(wù)的軌跡數(shù)據(jù)發(fā)布與現(xiàn)有的GNoise機(jī)制與PNoise機(jī)制進(jìn)行對(duì)比顯示在數(shù)據(jù)質(zhì)量和隱私保護(hù)度均取得良好的實(shí)驗(yàn)結(jié)果。
[Abstract]:With the rapid development of mobile positioning technology and mobile self-organizing network technology, car Networking (VANETs) technology has attracted domestic and foreign government attaches great importance to the academia and industry and has become a hot topic. At present, car networking and industrial 4, wearable devices become the three hotspot in networking field. Car networking the deployment can realize intelligent driving, traffic management and vehicle entertainment and so on. But the opportunities and challenges, the rapid development of networking in the car while also facing the risk of data security, privacy leaks. The future car networking in every car has more than 80 sensors, the amount of data transmission of cloud servers back every day can reach 100MB these data, covering the vehicle and the user's personal information, behavior patterns and other sensitive information, an attacker can broadcast messages, eavesdropping on communication in the process of data analysis, trajectory, vehicle tracking A vehicle to obtain sensitive data. The user's personal privacy and personal safety will be threatened. Therefore, to large-scale deployment of car networking, privacy and security the first problem faced is the data, and for the car networking, the trajectory data of the primary data is the vehicle. This paper based on the Internet of vehicles the potential path privacy requirement analysis system. Aiming at the car networking trajectory privacy issues under different scenarios are analyzed, in order to protect the car networking track data privacy and prevent sensitive information leakage are described, respectively introduces the analysis comparison of the existing privacy protection scheme by the mainstream technology and privacy protection, and to illustrate the problem. Aiming at the car networking trajectory privacy issues, network network data transfer and data release process of two kinds of application respectively in the car The scene, introducing difference privacy protection privacy points thought of vehicle network trajectory data release process, through theoretical analysis, modeling and experiment, to explore suitable car networking trajectory privacy protection mechanism. Finally, from two aspects of data quality and track data availability, performance evaluation of privacy protection algorithm is proposed in this paper and compared with the existing privacy protection scheme. Experimental results show that the differential privacy and privacy protection is not only a good effect can effectively relieve the pressure in the car networking communication within the network path of privacy protection, to track data in location based services released comparison shown in the data quality and the privacy protection degree achieved good results with GNoise the mechanism and the existing PNoise mechanism.

【學(xué)位授予單位】：河南工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP309

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本文編號(hào)：1365733