加權社交網(wǎng)絡中權重序列與最短路徑隱私保護算法研究.pdf

1、學位論文獨創(chuàng)性聲明本人聲明所呈交的論文是本人在導師指導下進行的研究工作及取得的研究成果。據(jù)我所知，除了文中特別加以標注和致謝的地方外，論文中不包含其他人已經(jīng)發(fā)表或撰寫過的研究成果， 也不包含已獲得江西理工大學或其他教育機構的學位或證書而使用過的材料。 與我一同工作的同志對本研究所做的任何貢獻均已在論文中做了明確的說明并表示謝意。申請學位論文與資料若有不實之處，本人承擔一切相關責任。研究生簽名： 時間： 年 月 日學位論文版權使用授權書本

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3、文在解密后適用本授權書。學位論文作者簽名（手寫）： 導師簽名（手寫）：簽字日期： 年 月 日 簽字日期： 年 月 日AbstractIIAbstractWith the changes of people’s lifestyles and communication methods, the socialnetwork covers a large number of related information such as indivi

4、duals andenterprises on the basis of information technology. Due to the analysis and applicationof various fields in scientific research and data mining of data in social networks willlead to the leakage of a large numbe

5、r of users' privacy. Among them, due to theweight of the weighted network and the leakage of users' privacy caused by theshortest path, it is gradually becoming the focus and difficulty of the research onprivacy

6、protection. The attacker will use the edge weight sequence to identify thenode. At the same time, the existing methods for privacy protection of the shortestpath have great changes to the network structure and cannot gua

7、rantee the validity ofsocial network data. Based on the proposed problem, this paper proposes a moreeffective defense algorithm for the weighted sequence and the attribute attacks of theshortest path in weighted social n

8、etworks. The main contents of this paper are asfollows:1. Weighted privacy protection of existing weighted social networks is mainlybased on the use of Gaussian multiplication and histogram anonymity methods toconstruct

9、the network, lack of research on privacy leakage caused by the weightedsequence of edges, and insufficient consideration of data validity. Based on this, thispaper will use the vector set to combine the distance between

10、the inner diameter of thegroup and the relative distance of the nodes to achieve the privacy protection of theweight sequence. The algorithm can guarantee data validity of the data and resist theweight sequence attack.2.

11、 On the basis of k ? anonymity, privacy protection is established by addingedges or deleting edges to construct k ? shortest path. This method has a greatinfluence on the structure of social networks, and the shortest pa

12、th privacy levelbetween each node pair only is k . It can only be said. Based on this, this articleclassifies all edges in the network into three categories: unvisited edges ? ? NE ,partially accessed edges ? ? PE and mu

13、st-accessed edges ? ? ME , and adjusts the edgesby the weight ratio policy. If no k paths fulfills the requirement of at least k theshortest path, the algorithm returns the current result directly and uses the privacylev