本文選題：移動(dòng)展業(yè)　切入點(diǎn)：隱私保護(hù)　出處：《武漢理工大學(xué)》2015年碩士論文

【摘要】：移動(dòng)互聯(lián)網(wǎng)時(shí)代的到來(lái)改變了人們工作、生活的方式,也給保險(xiǎn)行業(yè)帶來(lái)了新的機(jī)遇和挑戰(zhàn)。利用移動(dòng)終端開(kāi)展保險(xiǎn)業(yè)務(wù)成為一種新的保險(xiǎn)營(yíng)銷(xiāo)模式,它能幫助代理人快速完成保險(xiǎn)產(chǎn)品推薦、投保、查勘、理賠等一系列保險(xiǎn)流程。然而,移動(dòng)應(yīng)用在帶來(lái)方便的同時(shí)也存在諸多安全隱患,其中用戶隱私泄露問(wèn)題尤其嚴(yán)重。學(xué)術(shù)界對(duì)隱私保護(hù)問(wèn)題的研究由來(lái)已久,一般集中在數(shù)據(jù)庫(kù)應(yīng)用領(lǐng)域,包括基于數(shù)據(jù)挖掘和數(shù)據(jù)發(fā)布的隱私保護(hù)技術(shù),相關(guān)的理論如k-匿名模型、信息損失度等已經(jīng)較為成熟。然而,當(dāng)前隱私保護(hù)技術(shù)大多還停留在理論研究上,并沒(méi)有被廣泛運(yùn)用到實(shí)際應(yīng)用中,這一方面是由于相關(guān)的法律要求還不夠完善,另一方面在于用戶、應(yīng)用開(kāi)發(fā)商對(duì)隱私保護(hù)不夠重視。因此,如何針對(duì)具體的應(yīng)用在已有的安全和隱私保護(hù)技術(shù)基礎(chǔ)上進(jìn)行改進(jìn)與創(chuàng)新,使其滿足實(shí)際應(yīng)用的需求更具有現(xiàn)實(shí)意義。本文以移動(dòng)展業(yè)平臺(tái)項(xiàng)目為背景,介紹了傳統(tǒng)的數(shù)據(jù)發(fā)布中隱私保護(hù)相關(guān)理論和技術(shù),并對(duì)Android移動(dòng)平臺(tái)及其數(shù)據(jù)隱私保護(hù)技術(shù)進(jìn)行了簡(jiǎn)要描述,然后針對(duì)移動(dòng)展業(yè)應(yīng)用的具體需求設(shè)計(jì)了一套細(xì)粒度的隱私保護(hù)方案,包括隱私文件的備份、基于Hash加鹽的密碼保護(hù)以及面向數(shù)據(jù)發(fā)布的個(gè)性化匿名模型和算法。針對(duì)移動(dòng)展業(yè)應(yīng)用中的客戶資料等本地隱私數(shù)據(jù)的備份需求,設(shè)計(jì)了一種基于文件字節(jié)拆分和重組的備份方法,該方法將原始文件拆分成多份密文,并依次進(jìn)行本地備份和云備份。由于字節(jié)變換的過(guò)程比傳統(tǒng)加密算法簡(jiǎn)單,而且不需要管理密鑰,因此在性能上較之傳統(tǒng)的安全備份方法更加適用于移動(dòng)應(yīng)用。針對(duì)保險(xiǎn)公司可能將用戶的保單數(shù)據(jù)對(duì)外發(fā)布或共享的情況,在現(xiàn)有的匿名模型的基礎(chǔ)上提出了改進(jìn)的個(gè)性化(α,L)匿名模型和基于聚類(lèi)的實(shí)現(xiàn)算法,并運(yùn)用公開(kāi)數(shù)據(jù)集對(duì)其進(jìn)行了實(shí)驗(yàn),結(jié)果表明該算法在時(shí)間性能和數(shù)據(jù)信息損失度方面較之已有的聚類(lèi)匿名算法效果更好。最后,對(duì)本文的工作進(jìn)行了總結(jié),指出下一步需要從文件備份的安全性、面向動(dòng)態(tài)數(shù)據(jù)集的隱私保護(hù)等方向?qū)Ρ疚牡姆桨高M(jìn)行改進(jìn)。
[Abstract]:The advent of mobile Internet has changed the way people work and live, and has brought new opportunities and challenges to the insurance industry.Using mobile terminal to carry out insurance business has become a new insurance marketing model, which can help agents to complete a series of insurance processes such as insurance product recommendation, insurance, investigation, claim settlement and so on.However, mobile applications not only bring convenience, but also have a lot of security risks, among which, the problem of user privacy disclosure is especially serious.The research on privacy protection in academic circles has a long history. It is generally concentrated in the application field of database, including privacy protection technology based on data mining and data publishing. Related theories such as k- anonymity model, information loss degree and so on have been more mature.However, most of the current privacy protection technologies remain in the theoretical research, and have not been widely used in practical applications, this is due to the relevant legal requirements are not perfect, on the other hand, the user,Application developers pay less attention to privacy protection.Therefore, how to improve and innovate the existing security and privacy protection technologies in order to meet the needs of practical applications has more practical significance.Based on the mobile exhibition platform project, this paper introduces the traditional theory and technology of privacy protection in data release, and briefly describes the Android mobile platform and its data privacy protection technology.Then a set of fine-grained privacy protection schemes are designed to meet the specific needs of mobile exhibition applications, including backup of privacy files, password protection based on Hash salt, and personalized anonymous model and algorithm for data publishing.Aiming at the backup requirement of local privacy data such as customer data in mobile exhibition application, a backup method based on file byte splitting and recombination is designed, which divides the original file into several ciphertext.And then local backup and cloud backup.Because the process of byte transformation is simpler than the traditional encryption algorithm and the management key is not required, it is more suitable for mobile applications than the traditional secure backup method.Aiming at the situation that the insurance company may publish or share the user's policy data, an improved personalized (偽 -L-based) anonymous model and a clustering based implementation algorithm are proposed on the basis of the existing anonymous model.The experimental results show that the proposed algorithm is more effective than the existing clustering anonymous algorithm in terms of time performance and loss of data information.Finally, the work of this paper is summarized, and it is pointed out that the next step is to improve the scheme from the aspects of file backup security, privacy protection for dynamic data sets, and so on.
【學(xué)位授予單位】：武漢理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：TP309

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