An Early Fraud Detection Mechanism for Online Auctions Based on Phased Modeling

[[abstract]]Reputation systems provided by online auction sites are the only countermeasure available for buyers to evaluate a seller's credit. Unfortunately, feedback score mechanisms are too easily manipulated creating falsely overrated reputations. Therefore, developing an effective fraud detection method can assist the user in identifying cases of fraud. However, none of existing research addresses the most important issue of early fraud detection, which is, discovering a fraudster before he defrauds. For effective early fraud detection for online auctions, this paper proposes a novel phased detection framework to identify a potential fraudster as early as possible. To heighten precision in detection, different quantifiable behavioral features were extracted and integrated with regression model trees to build phased fraud behavior models. To demonstrate the effectiveness of the proposed method, real transaction data were collected from Taiwan's Yahoo!Kimo for training and testing. The experimental results with these models show that the recall rate of fraud detection is over 82%.[[sponsorship]]IEEE Taipei Section; National Science Council; Ministry of Education; Tamkang University; Asia University; Providence University; The University of Aizu; Lanzhou University[[conferencetype]]國際[[conferencedate]]20091203~20091205[[iscallforpapers]]Y[[conferencelocation]]Taipei, Taiwa

Inefficiencies in Digital Advertising Markets

Digital advertising markets are growing and attracting increased scrutiny. This article explores four market inefficiencies that remain poorly understood: ad effect measurement, frictions between and within advertising channel members, ad blocking, and ad fraud. Although these topics are not unique to digital advertising, each manifests in unique ways in markets for digital ads. The authors identify relevant findings in the academic literature, recent developments in practice, and promising topics for future research

Critical success factors for preventing E-banking fraud

E-Banking fraud is an issue being experienced globally and is continuing to prove costly to both banks and customers. Frauds in e-banking services occur as a result of various compromises in security ranging from weak authentication systems to insufficient internal controls. Lack of research in this area is problematic for practitioners so there is need to conduct research to help improve security and prevent stakeholders from losing confidence in the system. The purpose of this paper is to understand factors that could be critical in strengthening fraud prevention systems in electronic banking. The paper reviews relevant literatures to help identify potential critical success factors of frauds prevention in e-banking. Our findings show that beyond technology, there are other factors that need to be considered such as internal controls, customer education and staff education etc. These findings will help assist banks and regulators with information on specific areas that should be addressed to build on their existing fraud prevention systems

Using Clustering Techniques to Analyze Fraudulent Behavior Changes in Online Auctions

[[abstract]]Schemed fraudsters often flip behavior in terms of circumstances change as camouflage for disguising malicious actions in online auctions. For instance, the fake transaction records interwoven with real trades are indistinguishable from legitimate transaction histories. The ways of fraudulent behavior changes formulate different types of tricks for swindling. To avoid trading with fraudsters, recognizing the types of fraudulent behavior changes in advance is helpful in choosing appropriate trading partners. Therefore, in order to distinguish the types of behavior changes from different fraudsters, clustering techniques were applied such as X-Means for grouping in characteristics. Afterwards, C4.5 decision trees were employed for inducing the rules of the labeled clusters. In this study, the real transaction data of 236 proven fraudsters was collected from Yahoo!Taiwan for testing. The experimental results demonstrate that the fraudsters are categorized into 4 natural groups and the vast majority of fraudster, 93% of fraudsters on average, follows certain default models to develop a scam. The findings of this study also make online auction early fraud detection possible.[[conferencetype]]國際[[conferencedate]]20100611~20100613[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]Manila, Philippin

Cyber-crime Science = Crime Science + Information Security

Cyber-crime Science is an emerging area of study aiming to prevent cyber-crime by combining security protection techniques from Information Security with empirical research methods used in Crime Science. Information security research has developed techniques for protecting the confidentiality, integrity, and availability of information assets but is less strong on the empirical study of the effectiveness of these techniques. Crime Science studies the effect of crime prevention techniques empirically in the real world, and proposes improvements to these techniques based on this. Combining both approaches, Cyber-crime Science transfers and further develops Information Security techniques to prevent cyber-crime, and empirically studies the effectiveness of these techniques in the real world. In this paper we review the main contributions of Crime Science as of today, illustrate its application to a typical Information Security problem, namely phishing, explore the interdisciplinary structure of Cyber-crime Science, and present an agenda for research in Cyber-crime Science in the form of a set of suggested research questions

Exploring Information Disclosure In Online Auctions

This research examines how a seller’s reputation score and auction pre-configuration affects people’s participation in communication within online auction communities. A leading horizontal intermediary auction platform is used to conduct this research. Its seller “feedback” mechanism and “ask seller a question” forum are chosen as representatives of post- and intra-transactional information disclosure. A self-developed classification approach is used to classify the buyer-initiated questions. The results of multinomial logistic regression indicate that product quality, shipment and payment issues are aspects that concern buyers the most in the early stages of an auction. Subsequently, their attention is likely to shift to seller credibility and price negotiations as listing durations get longer. In terms of the influ- ence of seller feedback ratings, our findings suggest that lower-rated traders are more likely to be asked questions about product description and seller credibility. Buyer concern about seller uncertainty is only alleviated if the seller has a good reputation. Even medium-rated sellers are suspected of being opportunistic. Moreover, buyers are more willing to discuss transaction-related issues and raise negotiation-associated questions with sellers who have already achieved high reputation scores. Finally, the theoretical and managerial implications are elaborated

Two case studies on electronic distribution of government securities: the U.S. Treasury Direct System and the Philippine Expanded Small Investors Program

The case study on the U.S. Treasury Direct examines the evolution of the electronic distribution systems for marketable and nonmarketable government securities, the main objectives, and the basic legal infrastructure and the preconditions enabling the system. The U.S. experience highlights that the enabling environment and infrastructure (for example, in terms of information databases such as Pay.Gov) make a large difference in terms of both the security and convenience that customers can expect in the use of the system. The system also achieved important cost savings for the Bureau of the Public Debt. The case study on the Small Investors Program of the Philippines looks at a program that the Philippine government has been experimenting with to sell its securities directly to retail investors over the Internet. The recently revised version of the program-called the Expanded Small Investors Program-aims to increase access to government securities and distribute them more widely, develop better savings products, and enhance competition in the primary markets for these securities. The authors analyze whether the program's main goals can be achieved while mitigating the risks. Their analysis suggests thatthere are good reasons to believe that the new program will succeed. Still, regular and responsive assessments and adjustments will be required as the program moves forward.International Terrorism&Counterterrorism,Environmental Economics&Policies,Fiscal&Monetary Policy,Payment Systems&Infrastructure,Financial Intermediation,Environmental Economics&Policies,Financial Intermediation,Insurance&Risk Mitigation,Public Sector Economics&Finance,Banks&Banking Reform

Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting

The most significant progress in recent years in online display advertising is what is known as the Real-Time Bidding (RTB) mechanism to buy and sell ads. RTB essentially facilitates buying an individual ad impression in real time while it is still being generated from a user’s visit. RTB not only scales up the buying process by aggregating a large amount of available inventories across publishers but, most importantly, enables direct targeting of individual users. As such, RTB has fundamentally changed the landscape of digital marketing. Scientifically, the demand for automation, integration and optimisation in RTB also brings new research opportunities in information retrieval, data mining, machine learning and other related fields. In this monograph, an overview is given of the fundamental infrastructure, algorithms, and technical solutions of this new frontier of computational advertising. The covered topics include user response prediction, bid landscape forecasting, bidding algorithms, revenue optimisation, statistical arbitrage, dynamic pricing, and ad fraud detection