資料載入處理中...
臺灣人文及社會科學引文索引資料庫系統
:::
網站導覽
國圖首頁
聯絡我們
操作說明
English
行動版
(3.145.28.103)
登入
字型:
**字體大小變更功能,需開啟瀏覽器的JAVASCRIPT,如您的瀏覽器不支援,
IE6請利用鍵盤按住ALT鍵 + V → X → (G)最大(L)較大(M)中(S)較小(A)小,來選擇適合您的文字大小,
如為IE7以上、Firefoxy或Chrome瀏覽器則可利用鍵盤 Ctrl + (+)放大 (-)縮小來改變字型大小。
來源文獻查詢
引文查詢
瀏覽查詢
作者權威檔
引用/點閱統計
我的研究室
資料庫說明
相關網站
來源文獻查詢
/
簡易查詢
/
查詢結果列表
/
詳目列表
:::
詳目顯示
第 1 筆 / 總合 1 筆
/1
頁
來源文獻資料
摘要
外文摘要
引文資料
題名:
以行為狀態變遷為基礎之線上拍賣詐騙偵測方法
書刊名:
資訊管理學報
作者:
張昭憲
/
莊秉諺
作者(外文):
Chang, Jau-shien
/
Jhuang, Bing-yan
出版日期:
2017
卷期:
24:1
頁次:
頁97-130
主題關鍵詞:
詐騙偵測
;
網路詐騙
;
線上拍賣
;
資料探勘
;
電子商務
;
Fraud detection
;
Internet fraud
;
Online auction
;
Data mining
;
E-commerce
原始連結:
連回原系統網址
相關次數:
被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
排除自我引用:0
共同引用:
1
點閱:30
近年來,線上拍賣的蓬勃發展有目共睹。線上拍賣交易兼具便利性與隱蔽性,且不受時間與空間的限制,使得交易量逐年顯著提升。然而,面對如此蓬勃的交易平台,許多詐騙者開始混雜其中,謀取不法利益。詐騙的方式不但多樣化,且經常隨著時間、環境改變,令人防不勝防。為了協助交易者早期發現詐騙陷阱,避免蒙受不必要的損失,本研究以行為狀態分析為基礎,發展了一套線上拍賣詐騙偵測與預警方法。首先,針對詐騙者及正常者的交易記錄進行時序切割,再對其特徵值向量進行分群,以歸納出典型的交易者狀態。而後,針對資料集中所有的交易歷史進行狀態變遷切割,以產生與時序行為相關的偵測模型。在此同時,我們也利用狀態切割後的資料集,製作狀態標籤字串,並產生循序樣式,供使用者比對、監控可疑帳號。根據上述方法,本研究實作了一套簡易的線上拍賣交易輔助系統,輔助使用者在交易前觀察、分析交易對象的行為。為了驗證提出方法之有效性,本研究使用拍賣網站實際交易資料進行實驗,結果顯示本研究提出之方法確實有助於提升詐騙偵測之準確性與預警能力。
以文找文
Purpose-The fraudsters’ strategies of online auctions are diverse and changing rapidly. It results in the difficulty of fraud detection and prevention. The purpose of this paper is to develop effective methods to help discovering online auction fraud as early as possible. Design/methodology/approach-This paper develops effective detection methods based on behavioral state transition of fraudsters. First, we partition and duplicate the transaction histories of traders according to trading events. Then, a reduction method based on state transition is developed to reduce the size of data set, which is then used to build the detection model. In addition, the state label strings are used to conduct the behavioral patterns of suspects for monitoring. Findings-To demonstrate the effectiveness of the proposed methods, real transaction data are gathered from online auction sites for experiments. The results show that our methods do increase the detection accuracy and demonstrate that the early fraud detection by behavioral monitoring is possible. Research limitations/implications-The limitations of this work is that the proposed method could be ineffective for the fraudsters who steal or buy other normal accounts for disguise. Albeit being difficult, it is still possible to discover them by monitoring their behavioral changes in some critical time point. Certainly, it needs newly-developed detection methods. Practical implications-If the developed methods can be implemented and incorporated into the routine tasks of real online auction sites, the efforts of monitoring abnormal traders can be greatly reduced and the cost of maintaining a smooth trading environment can drop significantly. As a result, the fraud events will be effectively suppressing and the users will have more confidence in trading with online auctions. Originality/value-To apply state transition concept to detect latent fraudsters, which extends intuitive decision tree and other learning models to more complicated time-based analysis. Thus, based on the proposed novel approaches, new methods can be developed to discover more well-camouflaged fraudsters.
以文找文
期刊論文
1.
Gavish, B.、Tucci, C.(2008)。Reducing Internet auction fraud。Communications of the ACM,51(5),89-97。
2.
Goes, P. B.、Tu, Y.、Tung, A.(2009)。Online auctions hidden metrics。Communications of the ACM,52(4),147-149。
3.
Pavlou, P. A.、Dimoka, A.(2006)。The nature and role of feedback text comments in online marketplaces: implications for trust building, price premiums, and seller differentiation。Information Systems Research,17(4),392-414。
4.
Chang, W. H.、Chang, J. S.(2012)。An Effective Early Fraud Detection Method for Online auctions。Electronic Commerce Research and Applications,11(4),346-360。
5.
王俊程、邱垂鎮、葛煥元(20051000)。以交易記錄的社會網絡結構建立線上拍賣哄抬評價的偵測指標。資訊管理學報,12(4),143-184。
延伸查詢
6.
Chandola, V.、Banerjee, A.、Kumar, V.(2009)。Anomaly Detection: A Survey。ACM Computing Surveys,41(3)。
7.
Chang, J. S.、Wong, H. J.(2011)。Selecting appropriate sellers in online auctions through a multi-attribute reputation calculation method。Electronic Commerce Research and Applications,10(2),144-154。
8.
Chang, W. H.、Chang, J. S.(2011)。A Novel Two-Stage Phased Modeling Framework for Early Fraud Detection in Online Auctions。Expert Systems with Applications,38(9),11244-11260。
9.
Chua, C. E.、Wareham, J.(2004)。Fighting Internet Auction Fraud: An Assessment and Proposal。Computer,37(10),31-37。
10.
Kaszuba, T.、Hupa, A.、Wierzbicki, A.(2010)。Advanced Feedback Management for Internet Auction Reputation Systems。IEEE Internet Computing,14(5),31-37。
11.
Kobayashi, M.、Ito, T.(2007)。A transactional relationship visualization system in internet auctions。IEEE Computer Society,248-251。
12.
Kobayashi, M.、Ito, T.(2008)。A Transactional Relationship Visualization System in Internet Auctions。Electronic Commerce-Studies in Computational Intelligence,110,87-99。
13.
Levenshtein, V. I.(1965)。Binary codes capable of correcting deletions, insertions, and reversals。Soviet Physics Dokl,10,707-710。
14.
Schmidt, S.、Steele, R.、Dillon, T.、Chang, E.(2007)。Fuzzy trust evaluation and credibility development in multi-agent systems。Applied Soft Computing,7(2),492-505。
15.
Selvaraj, C.、Anand, S.(2012)。A Survey on Security Issues of reputation Management Systems for Peer-to-Peer Networks。Computer Science Review,6,145-160。
16.
Sherchan, Wanita、Nepal, Surya、Paris, C.(2013)。A Survey of Trust in Social Networks。ACM Computing Surveys,45(4),(47)1-(47)33。
17.
Tavakolifard, M.、Almeroth, K. C.(2012)。Social Computing: An Intersection of recommender Systems, Trust/Reputation Systems, and Social Network。IEEE Network,26(4),53-58。
18.
Yu, L.、Liu, H.(2004)。Efficient Feature Selection via Analysis of Relevance and Redundancy。Journal of Machine Learning Research,5,1205-1224。
19.
Quinlan, J. R.(1986)。Induction of Decision Trees。Machine Learning,1(1),81-106。
會議論文
1.
Chang, J. S.、Chang, W. H.(2009)。An Early Fraud Detection Mechanism for Online Auctions Based on Phased Modeling。The 2009 International Workshop on Mobile Systems E-commerce and Agent Technology,(會議日期: 2009/12/03-2009/12/05),743-748。
2.
Chau, D. H.、Pandit, S.、Faloutsos, C.(2006)。Detecting fraudulent personalities in networks of online auctioneers。10th European Conference on Principles and Practice of Knowledge Discovery in Databases: PKDD 2006,(會議日期: 2006/09/18-2006/09/22)。Springer-Verlag。103-114。
3.
Pandit, S.、Chau, D. H.、Wang, S.、Faloutsos, C.(2007)。NetProbe: A fast and scalable system for fraud detection in online auction networks。The 16th International Conference on World Wide Web,(會議日期: 2007/05/08-2007/05/12),201-210。
4.
Zhang, B.、Zhou, Y.、Faloutsos, C.(2008)。Toward a comprehensive model in Internet auction fraud detection。The 41st Annual Hawaii International Conference on System Sciences,(會議日期: 2008/07/07-2008/07/10)。Waikoloa, HI。1-9。
5.
Agrawal, R.、Srikant, R.(1995)。Mining Sequential Patterns。The Eleventh International Conference on Data Engineering,(會議日期: 1995/03/06-1995/03/10),3-14。
6.
Srikant, R.、Agrawal, R.(1996)。Mining Sequential Patterns: Generalizations and Performance Improvements。Advances in Database Technology Edbt '96: 5th International Conference on Extending Database Technology,(會議日期: 1996/03/25-1996/03/29),3-17。
7.
Fawcett, T.、Provost, F.(1999)。Activity Monitoring: Noticing Interesting Changes in Behavior。The Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,(會議日期: 1999/08/15-1999/08/18)。San Diego, CA。53-62。
8.
Brown, D. E.、Oxford, R. B.(2001)。Data Mining Time Series with Applications to Crime Analysis。The 2001 IEEE conference,(會議日期: 2001/10/07-2001/10/10)。Tucson, Arizona。1453-1458。
9.
Chang, W. H.、Chang, J. S.(2010)。A Multiple-Phased Modeling Method to Identify Potential Fraudsters in Online Auctions。The 2nd International Conference on Computer Research and Development,(會議日期: 2010/05/07-2010/05/10)。Kuala Lumpur。186-190。
10.
Chang, W. H.、Chang, J. S.(2010)。An Online Auction Fraud Screening Mechanism for Choosing Trading Partners。2010The 2nd International Conference on Education Technology and Computer,(會議日期: 2010/06/22-2010/06/24)。Shanghai。V5-56。
11.
Chau, D. H.、Faloutsos, C.(2005)。Fraud Detection in Electronic Auction。European Web Mining Forum (EWMF 2005) at ECML/PKDD,(會議日期: 2005/10/03-2005/10/07)。Porto。87-97。
12.
Ishioka, T.(2005)。An expansion of x-means for automatically determining the optimal number of clusters-progressive iterations of k-means and merging of the clusters。Fourth IASTED international conference computational intelligence,(會議日期: 2005/07/04-2005/07/06)。Calgary, Alberta。91-96。
13.
Pei, J.(2001)。PrefixSpan: Mining sequential patterns efficiently by prefix- projected pattern growth。International Conference on Data Engineering,(會議日期: 2001/04/02-2001/04/06)。Heidelberg。215-224。
14.
Pei, J.、Han, J.、Wang, W.(2002)。Mining Sequential Patterns with Constraints in Large Databases。The eleventh international conference on Information and knowledge management,(會議日期: 2002/11/04-2002/04/09)。McLean, Virginia。18-25。
15.
Pelleg, D.、Moore, A.(2000)。X-means: Extending K-means with Efficient Estimation of the Number of Clusters。The 17th International Conference on Machine Learning,(會議日期: 2000/06/29-2000/07/02)。San Francisco, CA。727-734。
16.
Wang, J.、Chiu, C.(2005)。Detecting Online Auction Inflated-Reputation Behaviors using Social Network Analysis。NAACSOS Conference,(會議日期: 2005/06/26-2005/06/28)。Indiana。26-28。
圖書
1.
Quinlan, J. R.(1993)。C4.5: Programs for Machine Learning。California:Morgan Kaufmann Publisher。
2.
Witten, Ian H.、Frank, Eibe(2005)。Data Mining: Practical Machine Learning Tools and Techniques。Amsterdam:Morgan Kaufmann。
其他
1.
National White Collar Crime Center(2009)。2008 Internet Crime Report,http://www.ic3.gov/media/annualreport/2008_IC3Report.pdf。
2.
National White Collar Crime Center(2011)。2010 Internet Crime Report,http://www.ic3.gov/media/annualreport/2010_IC3Report.pdf。
3.
National White Collar Crime Center(2012)。2011 Internet Crime Report,http://www.ic3.gov/media/annualreport/2011_IC3Report.pdf。
4.
DJ Project(2014)。Java Web Browser,http://djproject.sourceforge.net/ns/。
5.
eBay Inc.(1995)。How Feedback works,http://pages.ebay.com/help/feedback/howitworks.html。
6.
eBay Inc.(2013)。Quarterly Report,http://investor.ebay.com/annuals.cfm。
7.
Weka(2014)。Weka 3-Data Mining with Open Source Machine Learning Software in Java,http://www.cs.waikato.ac.nz/ml/weka。
推文
當script無法執行時可按︰
推文
推薦
當script無法執行時可按︰
推薦
引用網址
當script無法執行時可按︰
引用網址
引用嵌入語法
當script無法執行時可按︰
引用嵌入語法
轉寄
當script無法執行時可按︰
轉寄
top
:::
相關期刊
相關論文
相關專書
相關著作
熱門點閱
1.
以模型融合為基礎之線上拍賣詐騙偵測
2.
淺談大數據、統計資訊分析與統計學習在臺灣金融服務業的運用
3.
線上拍賣策略對拍賣結果之影響--比較英式拍賣與Vickrey拍賣網站之出價方式
4.
利用探勘技術偵測線上拍賣異常喊價之競標者
5.
利用探勘技術發掘具有異常喊價傾向之競標者
6.
以交易記錄的社會網絡結構建立線上拍賣哄抬評價的偵測指標
7.
應用資料探勘於壽險業之客戶分群研究
1.
社會文本情況察覺用於公領域監測
2.
線上拍賣詐騙之有效偵測
3.
電子商務平台交易行為預測之研究
4.
使用顧客知識於行銷之決策支援系統
5.
電子商務環境中網路拍賣系統之研究
1.
客戶關係管理與資料探勘
無相關著作
1.
同儕壓力、知覺風險、顧客滿意度之結構模式研究--以科技接受模式為中介變項
2.
類神經網路投資組合策略績效之實證研究:以臺灣中型100電子股為例
3.
往復式高壓/真空成型機創新研發設計之研究
4.
移動虛擬社區用戶持續信息搜尋意願研究
5.
基於短語句法結構和依存句法分析的情感評價單元抽取
6.
臺灣社區通網站平臺使用頻率影響因素之研究:科技接受模型的觀點
7.
高職教師專業成長需求與研習參與態度之關係:以高屏地區教師為例
8.
虛擬代言人對廣告效果之影響:以產品類別、自我參照為干擾變數
9.
基於詞性組合規則結合維基百科進行中文命名實體辨識與消歧義
10.
一起來團購!團購意願前置因素之研究
11.
應用PPM理論探討高級進口車顧客之轉換意圖
12.
Factors for User Intention to Switch Browsers: A Cross-National Survey
13.
探討幼兒使用擴增實境學習形狀及顏色之科技接受模式及學習成效
14.
以卡片分類法探討女性消費者對健康食品包裝資訊之組織與分類研究
15.
大學生對個資之資訊需求與尋求分析
QR Code