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研究生:葉懿慧
研究生(外文):Yi-Hui Yeh
論文名稱:以社會網路分析方法偵測線上拍賣網站的詐欺共犯群體
論文名稱(外文):Detecting collusive fraud group in online auction by social network analysis
指導教授:林熙禎林熙禎引用關係
指導教授(外文):Shi-Jen Lin
學位類別:碩士
校院名稱:國立中央大學
系所名稱:資訊管理研究所
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:中文
論文頁數:55
中文關鍵詞:線上拍賣詐欺偵測詐欺共犯群體K-PlexN-Club社會網路分析
外文關鍵詞:Online AuctionK-PlexFraud Group DetectionSocial Network AnalysisN-Club
相關次數:
  • 被引用被引用:18
  • 點閱點閱:737
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  • 下載下載:212
  • 收藏至我的研究室書目清單書目收藏:5
由於網拍的可見商機與低進入成本,使得國內外網拍平台皆成為網路詐欺犯罪的溫床,其中常見的手法是大量建立帳號利用這些帳號建立假交易以增加彼此評價分數,雖不是直接造成交易方財產損失的詐欺方式,卻是實行詐欺前重要的取信手段。本研究針對此種詐欺共犯群體,提出一個模組化的詐欺共犯群體偵測流程,以彌補網路拍賣評價系統之不足。將流程分為前處理、分群、合併、過濾、比對五階段,其中在分群階段以社會網路分析分群方法之K-Plex與N-Club為主要方法。而系統各階段的設計過程中將以詐欺共犯群體之組織特性為基礎設計與調整各模組的實作方式。本研究從露天拍賣網站收集真實線上拍賣交易評價資料,並使用所提出之階段性的模組化偵測流程進行實做與驗證。
Due to the great profit and low entrance cost of online auction, there are a lot of online fraud cases in online auction sites. One of the most common fraud method is to establish several auction account, and using these account to have transactions with each other then increase their reputation.
The research focus on this kind of the collusive fraud group and propose a process to detect collusive group in order to complete the flaws of reputation system in the online auction. We divide the process into five steps: preprocessing, classification, merge, filter, and validation. In the step of classification, we use the K-Plex and N-Club approach of social network analysis as the primary method. Otherwise, in the design process of each step, we design and adjust the implementation of each module based on organizational characteristics of the collusive fraud group. In this research, we collect the real reputation data of online auction from "www.ruten.com.tw", and use the detective process we propose to do implementation and validation.
ABSTRACT
摘要
誌謝
目錄
圖目錄
表目錄
第一章 緒論
1-1研究背景
1-2研究動機
1-3研究目的
1-4研究方法
1-5論文架構
第二章 文獻探討
2-1拍賣與拍賣詐欺分類
2-2社會網路分析
2-3詐欺共犯群體之組織特性
2-4拍賣詐欺偵測方法
2-5 小結
第三章 系統設計
3-1系統假設
3-2分群方法之參數設定
3-3模型資料建立與測試
3-3系統模組流程說明
3-4 小結
第四章 系統實作與評估
4-1系統實做核心與細節
4-2實驗資料之來源與收集
4-4 小結
第五章 結論與未來研究方向
5-1結論與貢獻
5-2未來研究方向
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