【摘要】：作為網(wǎng)絡(luò)資源共享的典型代表，P2P（Peer-to-Peer）技術(shù)成為資源共享的最主要方式，用戶通過P2P技術(shù)共享音樂、電影、文檔和游戲等。P2P網(wǎng)絡(luò)中的盜版泛濫嚴(yán)重?fù)p害了數(shù)字媒體公司的利益。其中，“串通盜版”（即花錢購買資源的P2P客戶端免費(fèi)分享資源給其他用戶）背后的協(xié)同行為成為P2P版權(quán)的主要威脅源，學(xué)術(shù)界和工業(yè)界對(duì)這種威脅給予了關(guān)注。 研究P2P的版權(quán)問題可以歸結(jié)為如下兩種方式：第一種方式利用協(xié)議級(jí)簽名的方法來自動(dòng)識(shí)別和有害預(yù)防；第二種方式屬于應(yīng)用級(jí)監(jiān)管，需找出非法內(nèi)容和IP之間的關(guān)系進(jìn)行非實(shí)時(shí)的針對(duì)用戶的警告或處罰。值得注意的是，第一種方式是嵌入特定個(gè)人授權(quán)協(xié)議（例如PAP）到標(biāo)準(zhǔn)的P2P協(xié)議中，，而第二種方式在旨在不影響或不改變公認(rèn)開放共享特性的標(biāo)準(zhǔn)P2P協(xié)議。事實(shí)上，在工業(yè)化實(shí)施過程中，第二種方式更實(shí)用也更容易被各方接受。本論文研究工作屬于第二種方式的范疇，基于CBF(Count BloomFilter)對(duì)協(xié)同行為分析開展了針對(duì)性研究，其創(chuàng)新與特色主要包括以下內(nèi)容： 1.提出了一種MCBFC(Multi-Count-BloomFilter-Cycle)結(jié)構(gòu)存儲(chǔ)P2P用戶行為following關(guān)系，其中MCBFC是由時(shí)間標(biāo)簽和N個(gè)CBF組成的環(huán)狀結(jié)構(gòu)，每個(gè)CBF中的計(jì)數(shù)器Count都連接有一個(gè)鏈表，用戶行為following關(guān)系(U seri, R k, User j)經(jīng)哈希函數(shù)散列到相應(yīng)的鏈表中存儲(chǔ)； 2.提出了一種針對(duì)協(xié)同行為的基于內(nèi)容反饋的following分析方法。論文提出了PFCF(Probabilistic Following with Content Feedback)模型，并分析了PFCF模型部署位置，對(duì)PFCF模型中的MCBFC存儲(chǔ)結(jié)構(gòu)，提出了一種用戶行為關(guān)聯(lián)挖掘算法，算法通過檢測到的資源和用戶，挖掘用戶的相關(guān)行為，同時(shí)根據(jù)挖掘出來的用戶關(guān)聯(lián)行為數(shù)據(jù)進(jìn)行following概率分析以及基于內(nèi)容反饋的following概率分析，通過用戶行為following分析預(yù)防阻止P2P版權(quán)； 3.基于CBF和MCBFC兩種存儲(chǔ)結(jié)構(gòu)做了充分實(shí)驗(yàn)。主要從碰撞率、空間分配、時(shí)間復(fù)雜度三個(gè)方面進(jìn)行對(duì)比，驗(yàn)證了MCBFC結(jié)構(gòu)不僅比CBF結(jié)構(gòu)好的存儲(chǔ)效率，通過犧牲可容忍計(jì)算代價(jià)有效支撐歷史行為關(guān)系分析，而且MCBFC環(huán)存儲(chǔ)結(jié)構(gòu)可以保存一定時(shí)間的用戶行為歷史數(shù)據(jù)用于分析。
[Abstract]:As a typical representative of network resource sharing, P2P (Peer-to-Peer) technology has become the most important way of resource sharing. Users share music and movies through P2P technology. Documents and games. The proliferation of piracy in P2P networks has seriously damaged the interests of digital media companies. Among them, the collaborative behavior behind "collusion piracy" (that is, P2P clients who spend money to share resources with other users for free) has become the main source of P2P copyright threat, which has been paid attention to by academia and industry. The copyright problem of P2P can be summed up in the following two ways: the first way is to use the protocol level signature method to automatically identify and prevent harm; The second method belongs to application-level supervision, and it is necessary to find out the relationship between illegal content and IP to warn or punish users in non-real time. It is worth noting that the first way is to embed specific personal authorization protocols (such as PAP) into standard P2P protocols, while the second is in standard P2P protocols that do not affect or change recognized open sharing characteristics. In fact, in the process of industrialization, the second way is more practical and easier to accept. The research work of this paper belongs to the category of the second way. Based on CBF (Count BloomFilter), the research on collaborative behavior analysis is carried out. Its innovation and characteristics mainly include the following contents: 1. In this paper, a MCBFC (Multi-Count-BloomFilter-Cycle) structure is proposed to store P2P user behavior following relationship, in which MCBFC is a ring structure composed of time label and N CBF, and the counter Count in each CBF is connected with a linked list. The user behavior following relation (U seri, R k, User j) is hashed into the corresponding linked list by hash function. 2. A content feedback based following analysis method for collaborative behavior is proposed. In this paper, the PFCF (Probabilistic Following with Content Feedback) model is proposed, and the deployment location of PFCF model is analyzed. For the MCBFC storage structure in PFCF model, a user behavior association mining algorithm is proposed. Mining the related behavior of users, at the same time, according to the excavated user association behavior data, following probability analysis and following probability analysis based on content feedback are carried out, and the P2P copyright is prevented by user behavior following analysis. 3. Full experiments are carried out based on CBF and MCBFC storage structures. This paper mainly compares the collision rate, space allocation and time complexity, and verifies that the MCBFC structure is not only better than the CBF structure in storage efficiency, but also effectively supports the historical behavior relationship analysis by sacrificing the tolerable calculation cost. Moreover, the MCBFC ring storage structure can hold the historical data of user behavior for a certain period of time for analysis.
【學(xué)位授予單位】：北京工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.092

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