Peer to Peer Mobile Coupons: Adding Incentives without Sacrificing Security

Mobile commerce is flourishing today due to the advance of the mobile technology. Many conventional marketing activities are moving their ways to the mobile environment. Efficient marketing instruments such as the paper coupons and the electronic coupons are also evolving into the mobile coupons. In comparison with conventional coupons, mobile coupons are personalized and suitable for peer to peer delivery. Coupons are commonly issued by the merchants, used by the interested customers, and discarded by the uninterested receivers. Raising the redemption rate of the coupon will increase the sales of the promoted items. The raise can be accomplished by forwarding coupons from uninterested receivers to potentially interested customers. The ease-of-use exchange mechanism in mobile devices pushes the delivery in the peer to peer environment. Moreover, the characteristic of personalization inspires trust into mobile coupons. Thus, adding the incentives of coupon forwarding, such as a reward bonus, may activate the movement of stationary coupons and eventually increase the redemption rate of mobile coupons. Nevertheless, the incentives adding may bring the threats of alterations and forgery; if the adding mechanism is improperly made. Additionally, complicated security means are hindered by the limitations of storage space, computation power, and communication bandwidth of mobile devices. Therefore, we propose a scheme that uses digital signatures for verifying the incentive-added coupons and design a hash chain to detect possible forgery. The proposed scheme may increase the use of peer to peer mobile coupons without sacrificing the security

A Secure and Privacy-Preserving Targeted Ad-System

Thanks to its low product-promotion cost and its efficiency, targeted online advertising has become very popular. Unfortunately, being profile-based, online advertising methods violate consumers' privacy, which has engendered resistance to the ads. However, protecting privacy through anonymity seems to encourage click-fraud. In this paper, we define consumer's privacy and present a privacy-preserving, targeted ad system (PPOAd) which is resistant towards click fraud. Our scheme is structured to provide financial incentives to to all entities involved

Utilizando CAPTCHAs para Garantir a Segurança contra Fraudes no Marketing Digital / Utilizing CAPTCHA to Guarantee Security Against Fraud in Digital Marketing

Anunciar pela Internet é fundamental para o sucesso de diversos negócios hoje em dia. A Internet evoluiu para um ponto onde foi possível desenvolver um modelo de negócios para o marketing digital baseado em anúncios online, através da consolidação deste modelo de negócios. Entretanto, observa-se que alguns anunciantes de conteúdo são desonestos, usam ferramentas automáticas para gerar tráfego e lucram ao defraudar os anunciantes. Similarmente, alguns anunciantes usam ferramentas automáticas para clicar nos anúncios dos seus concorrentes, com o objetivo de esgotar o orçamento com marketing. Neste artigo, uma abordagem para prevenir a fraude de clique é proposta, através do uso de CAPTCHA clicáveis, diferentemente de diversas abordagens já estudadas anteriormente, que focam na detecção, uma vez que a fraude já tenha ocorrido

Securing Online Advertising

Online advertisement is a major source of revenues in the Internet. In this paper, we identify a number of vulnerabilities of current ad serving systems. We describe how an adversary can exploit these vulnerabilities to divert part of the ad revenue stream for its own benefit. We propose a scalable, secure ad serving scheme to fix this problem. We also explain why the deployment of this solution would benefit the Web browsing security in general

DETERMINATION OF CONSUMER’S ATTITUDES TOWARD MOBILE COUPONS AND A RESEARCH

Mobil teknolojilerin gelişmesi ile birlikte artık zaman ve yer kısıtlarına bağlı kalınmadan, teknolojiden ve beraberinde getirdiği yeniliklerden faydalanmak mümkün olmaktadır. İşletmeler kısa mesaj servisleri (SMS) başta olmak üzere iletişim ve satış geliştirme faaliyetleri için mobil hizmetlerden gitgide daha fazla faydalanmaya başlamışlardır. Malların, hizmetlerin ve fikirlerin tutundurulması sürecinde yararlanılan mobil pazarlama faaliyetlerinin bir parçası olan ve SMS aracılığı ile tüketicilerin mobil telefonlarına gönderilen mobil kuponlara son yıllarda ilgi artmıştır. Çalışmanın amacı, reklam, kişisel satış ve halkla ilişkiler faaliyetleri dışında kalan tüm tutundurma faaliyetlerini içeren satış geliştirme araçlarından birisi olan mobil kupon uygulamalarına ilişkin tüketici tutumlarını ortaya koymaktır. Araştırma mail adreslerine erişilebilen 400 mobil telefon kullanıcısına ulaşılarak yapılmış ve 383 mobil telefon kullanıcısından dönüş olmuştur. Anket formunda iki grup soru sorulmuştur. Tutumları ölçmeye yönelik sorular Astrıd Dickinger ve Mırella Kleıjnen’nın yapmış oldukları çalışmada yer alan sorular temel alınarakgeliştirilmiştir. Cevaplayıcıların anket sorularına ilişkin görüşlerinden elde edilen verilerin SPSS programı aracılığı ile analizi yapılmıştır. Araştırmaya katılan cevaplayıcıların mobil kupon kullanım oranının az olduğu tespit edilmiştir. Kupon kullanma eğilimi ve ekonomik fayda ile tavır ve sosyal normlar arasında anlamlı bir ilişki olduğu görülmektedir. Mobil Kuponların satış geliştirme aracı olarak kullanılması müşterilerin bir ekonomik fayda sağladığına inanması ve kendini özel olarak hissetmesi ile mümkündür. İşletmelerin müşterilerinin kendilerini özel hissetmelerini sağlayıcı ve mobil kupon değerini arttırıcı çabalara yer vermeleri gerekmektedir.Mobile technology, in every area of daily life, affects all age groups of people and increases its importance day by day. With development of mobile technologies, it can be possible that utilize the benefits of this technology and its innovations without limitation of time and place. Firms are increasingly using mainly Short Message Service (SMS) and mobile media for communication and promotion. In recent years, mobile coupons, which is one of the mobile marketing tools in the process of purchasing products and services, has been using as a promotion tools. There aren’t enough studies about via SMS with mobile coupons sent to consumers' mobile phones in Turkey. This study aims to determine the consumer’s attitude toward mobile coupons that is except for advertising, personal selling and public relations activities and sales developmenttools but includes all the promotional activities, trends of using mobile coupons and explain the factors which affect the using trend of consumers. In this study, sent a survey to 400 mobile phone users in Turkey and 383 mobile users responded the survey. The survey has included two groups of questions. One of them includes the demographic characteristics of consumers and the other one includes 33 questions which aims to measure of attitude of consumers. The questions of the second group were prepared the based on the study of Astrid DICKINGER and Mirella KLEIJNEN. The findings of the study is tested by using SPSS. It is found out that mobile coupon use among the answerers who participated the research is low. It is seen that there is a meaningful correlation between trend in coupon use and economic benefit with attitudeandsocialnorms. Thecustomers onlyfeel special when theybelievethemobile coupons as a sales development means provide economic benefit to theme. It is necessary for companies to put effort on making the customers feel special and improve the value of mobile coupons

Um protocolo criptográfico para auditoria de publicidade na web

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência de Computação.O objetivo deste trabalho é propor um protocolo criptográfico para auditoria de publicidade na Web

Click fraud : how to spot it, how to stop it?

Online search advertising is currently the greatest source of revenue for many Internet giants such as Google™, Yahoo!™, and Bing™. The increased number of specialized websites and modern profiling techniques have all contributed to an explosion of the income of ad brokers from online advertising. The single biggest threat to this growth is however click fraud. Trained botnets and even individuals are hired by click-fraud specialists in order to maximize the revenue of certain users from the ads they publish on their websites, or to launch an attack between competing businesses. Most academics and consultants who study online advertising estimate that 15% to 35% of ads in pay per click (PPC) online advertising systems are not authentic. In the first two quarters of 2010, US marketers alone spent $5.7 billion on PPC ads, where PPC ads are between 45 and 50 percent of all online ad spending. On average about$1.5 billion is wasted due to click-fraud. These fraudulent clicks are believed to be initiated by users in poor countries, or botnets, who are trained to click on specific ads. For example, according to a 2010 study from Information Warfare Monitor, the operators of Koobface, a program that installed malicious software to participate in click fraud, made over $2 million in just over a year. The process of making such illegitimate clicks to generate revenue is called click-fraud. Search engines claim they filter out most questionable clicks and either not charge for them or reimburse advertisers that have been wrongly billed. However this is a hard task, despite the claims that brokers\u27 efforts are satisfactory. In the simplest scenario, a publisher continuously clicks on the ads displayed on his own website in order to make revenue. In a more complicated scenario. a travel agent may hire a large, globally distributed, botnet to click on its competitor\u27s ads, hence depleting their daily budget. We analyzed those different types of click fraud methods and proposed new methodologies to detect and prevent them real time. While traditional commercial approaches detect only some specific types of click fraud, Collaborative Click Fraud Detection and Prevention (CCFDP) system, an architecture that we have implemented based on the proposed methodologies, can detect and prevents all major types of click fraud. The proposed solution analyzes the detailed user activities on both, the server side and client side collaboratively to better describe the intention of the click. Data fusion techniques are developed to combine evidences from several data mining models and to obtain a better estimation of the quality of the click traffic. Our ideas are experimented through the development of the Collaborative Click Fraud Detection and Prevention (CCFDP) system. Experimental results show that the CCFDP system is better than the existing commercial click fraud solution in three major aspects: 1) detecting more click fraud especially clicks generated by software; 2) providing prevention ability; 3) proposing the concept of click quality score for click quality estimation. In the CCFDP initial version, we analyzed the performances of the click fraud detection and prediction model by using a rule base algorithm, which is similar to most of the existing systems. We have assigned a quality score for each click instead of classifying the click as fraud or genuine, because it is hard to get solid evidence of click fraud just based on the data collected, and it is difficult to determine the real intention of users who make the clicks. Results from initial version revealed that the diversity of CF attack Results from initial version revealed that the diversity of CF attack types makes it hard for a single counter measure to prevent click fraud. Therefore, it is important to be able to combine multiple measures capable of effective protection from click fraud. Therefore, in the CCFDP improved version, we provide the traffic quality score as a combination of evidence from several data mining algorithms. We have tested the system with a data from an actual ad campaign in 2007 and 2008. We have compared the results with Google Adwords reports for the same campaign. Results show that a higher percentage of click fraud present even with the most popular search engine. The multiple model based CCFDP always estimated less valid traffic compare to Google. Sometimes the difference is as high as 53%. Detection of duplicates, fast and efficient, is one of the most important requirement in any click fraud solution. Usually duplicate detection algorithms run in real time. In order to provide real time results, solution providers should utilize data structures that can be updated in real time. In addition, space requirement to hold data should be minimum. In this dissertation, we also addressed the problem of detecting duplicate clicks in pay-per-click streams. We proposed a simple data structure, Temporal Stateful Bloom Filter (TSBF), an extension to the regular Bloom Filter and Counting Bloom Filter. The bit vector in the Bloom Filter was replaced with a status vector. Duplicate detection results of TSBF method is compared with Buffering, FPBuffering, and CBF methods. False positive rate of TSBF is less than 1% and it does not have false negatives. Space requirement of TSBF is minimal among other solutions. Even though Buffering does not have either false positives or false negatives its space requirement increases exponentially with the size of the stream data size. When the false positive rate of the FPBuffering is set to 1% its false negative rate jumps to around 5%, which will not be tolerated by most of the streaming data applications. We also compared the TSBF results with CBF. TSBF uses only half the space or less than standard CBF with the same false positive probability. One of the biggest successes with CCFDP is the discovery of new mercantile click bot, the Smart ClickBot. We presented a Bayesian approach for detecting the Smart ClickBot type clicks. The system combines evidence extracted from web server sessions to determine the final class of each click. Some of these evidences can be used alone, while some can be used in combination with other features for the click bot detection. During training and testing we also addressed the class imbalance problem. Our best classifier shows recall of 94%. and precision of 89%, with F1 measure calculated as 92%. The high accuracy of our system proves the effectiveness of the proposed methodology. Since the Smart ClickBot is a sophisticated click bot that manipulate every possible parameters to go undetected, the techniques that we discussed here can lead to detection of other types of software bots too. Despite the enormous capabilities of modern machine learning and data mining techniques in modeling complicated problems, most of the available click fraud detection systems are rule-based. Click fraud solution providers keep the rules as a secret weapon and bargain with others to prove their superiority. We proposed validation framework to acquire another model of the clicks data that is not rule dependent, a model that learns the inherent statistical regularities of the data. Then the output of both models is compared. Due to the uniqueness of the CCFDP system architecture, it is better than current commercial solution and search engine/ISP solution. The system protects Pay-Per-Click advertisers from click fraud and improves their Return on Investment (ROI). The system can also provide an arbitration system for advertiser and PPC publisher whenever the click fraud argument arises. Advertisers can gain their confidence on PPC advertisement by having a channel to argue the traffic quality with big search engine publishers. The results of this system will booster the internet economy by eliminating the shortcoming of PPC business model. General consumer will gain their confidence on internet business model by reducing fraudulent activities which are numerous in current virtual internet world

Secure and lightweight advertising on the Web

We consider how to obtain a safe and efficient scheme for Web advertising. We introduce to cryptography the market model, a common concept from economics. This corresponds to an assumption of rational behavior of protocol participants. Making this assumption allows us to design schemes that are highly efficient in the common case - which is, when participants behave rationally. We demonstrate such a scheme for Web advertising, employing the concept of e-coupons. We prove that our proposed scheme is safe and meets our stringent security requirements. (C) 1999 Published by Elsevier Science B.V. All rights reserved

ELSEVIER Abstract Secure and lightweight advertising on the Web

We consider how to obtain a safe and efficient scheme for Web advertising. We introduce to cryptography the market model, a common concept from economics. This corresponds to an assumption of rational behavior of protocol participants. Making this assumption allows us to design schemes that are highly efficient in the common case — which is, when participants behave rationally. We demonstrate such a scheme for Web advertising, employing the concept of e-coupons. We prove that our proposed scheme is safe and meets our stringent security requirements. © 1999 Publishe