Nos últimos anos, tem-se observado um aumento significativo no volume de transações financeiras realizadas pela Internet. Esse crescimento no volume financeiro, associado à fragilidade inerente à ausência de verificações básicas, possíveis somente em transações do mundo físico, tem atraído a atenção de pessoas com o objetivo de obter vantagens financeiras de forma ilícita. Devido aos prejuízos causados pelas fraudes, surgiram empresas de pagamento online com o objetivo de tornar as transações de compra e venda na Internet mais seguras. Essas empresas atuam como um intermediário das transações e assumem os riscos associados, mostrando-se ser esse um negócio de alto risco. Dado o alto volume de transações com as quais essas empresas precisam lidar, torna-se clara a necessidade de métodos computacionais para detecção de transações fraudulentas, visto que a utilização estrita de verificações manuais é inviável para lidar com tal volume de transações. Essa tarefa de análise e identificação de transações fraudulentas pode ser vista como um problema computacional de classificação, sendo então aplicáveis técnicas de classificação, aprendizado computacional e mineração de dados. Porém, dada a complexidade do problema, a aplicação de técnicas computacionais só é possível após um profundo entendimento do problema e a definição de uma modelagem eficiente associada a um processo consistente e abrangente, capaz de lidar com todas as etapas necessárias para a análise eficiente de uma transação. Face a isso, o presente trabalho propõe uma abordagem abrangente para tratar o problema da fraude nesse novo mercado de intermediação de pagamentos online utilizando como base um processo já muito bem estabelecido na indústria. Abordaremos mais especificamente uma das fases desse processo, que se refere justamente a utilização de ferramentas computacionais para a detecção das fraudes, e apresentaremos um sub-processo que envolve a utilização de várias ferramentas para o tratamento do ponto de vista computacional do problema de detecção de fraudes. Para a validação dos resultados da proposta, utilizaremos uma enorme quantidade de dados reais disponibilizados por uma grande empresa do setor de intermediação de pagamentos online que colaborou com nossa pesquisa. / In recent years, there has been a significant increase in the volume of electronic transactions in the Web. This growth in trading volume, associated with the risks caused by the absence of basic checks, possible only in transactions of the physical world, has attracted the attention of people with the intention of taking advantage to obtain illicit financial benefits. Due to the injuries caused by fraud, online payment service companies emerged, with the goal of making Web transactions safer. These companies act as an intermediary between buyers and sellers, assuming all the risks, and so it is clear that it is a high-risk business. Given the high volume of transactions with which these companies must deal, it is clear the need for computational methods for detecting fraudulent transactions, as the strict use of manual checks is infeasible to handle such a volume. The task of analysis and identification of fraudulent transactions can be seen as a classification problem, and so classification, data mining and machine learning techniques can be applied to it. However, given the complexity of the problem, the application of computational techniques is only possible after a thorough understanding of the problem and the definition of an efficient model, associated with a consistent and comprehensive process which would be able to handle all the steps needed to analyze a transaction in an efficient way. Given this scenario, this work proposes a comprehensive approach to address the problem of fraud in this new business of online payment intermediation, using as basis a process already established in the industry. We will discuss more specifically one of the phases of this process, which refers to the use of computational tools to detect frauds, and we will present a sub-process using several tools to deal with the problem from a computational point of view. To validate our results, we will use a huge amount of real data provided by an important company of the online payment industry, which cooperated with our research.

The work is about payment card systems. We’d like to describe infrastructure of credit cards, ATMs, POS terminals , focusing on the EMV standard. In theoretical part we will be introduced with the history and development of credit cards, ATMs and POS terminals. Then we focus on a detailed description of payments terminals and possibilities of payment via the Internet. The most extensive theoretical part deals width EMV standard. In practical part we will make our own program, which authenticates the user based on his credit card and it will allow the user to login in the system. Source codes of this application can be found on enclosed CD.

This doctoral thesis represents an investigation into financial fraud in online banking and card payment systems in the UK and China, involving network security, online financial transactions, internet fraud, card payment systems and individuals' perception of and behaviours towards electronic environments. In contrast to previous studies, the research questions were tackled by survey questionnaires both in the UK and China, with a particular interest in fraud and attempted fraud. The main findings from the UK respondents were that those with higher IT skill and younger respondents are more likely to be defrauded on the internet. Certain types of online activities are associated with higher risks of fraud, these being internet banking; online shopping and media downloading. Furthermore, four predictors (internet banking, online education services, downloading media and length of debit card usage) provided significant effects in the logistic regression model to explain fraud occurrence in the UK. Based on the data collected in China, younger respondents were more likely to have higher general IT skill and higher educational qualifications. However, online shopping was the only online activity which was significantly correlated to fraud occurrence. Finally, two predictors (frequency of usage of online shopping and number of debit cards) were selected in the logistic regression model to explain fraud occurrence in China.

Thesis describes technical and economic aspects of payment transaction using the empirical analysis on real data of payment institution. It focuses on the description of selected products provided by payment institution and empirically analyzes them on the basis of the available data in terms of the number of transactions in individual currencies, the ratio of product types utilization and clearing and settlement used by the payment institution. The thesis also describes the security requirements necessary for the conduct of payment transactions on the Internet for non-technically educated audiences. At the end of the thesis there are several recommendations for the development of payment institution based on empirical knowledge from data analysis, which can be used for further analysis of the payment institution.

Depuis ses fondements, le domaine de l’Interaction Homme-Machine (IHM) est marqué par le souci constant de concevoir et de produire des systèmes numériques utiles et utilisables, c’est-à-dire adaptés aux utilisateurs dans leur contexte. Vu le développement exponentiel des recherches dans les IHM, deux états des lieux s’imposent dans les environnements en ligne : le concept de confiance et le comportement de l’usager. Ces deux états ne cessent de proliférer dans la plupart des solutions conçues et sont à la croisée des travaux dans les interfaces de paiements en ligne et dans les systèmes de recommandation. Devant les progrès des solutions conçues, l’objectif de cette recherche réside dans le fait de mieux comprendre les différents enjeux dans ces deux domaines, apporter des améliorations et proposer de nouvelles solutions adéquates aux usagers en matière de perception et de comportement en ligne. Outre l’état de l’art et les problématiques, ce travail est divisé en cinq parties principales, chacune contribue à mieux enrichir l’expérience de l’usager en ligne en matière de paiement et recommandations en ligne : • Analyse des multi-craintes en ligne : nous analysons les différents facteurs des sites de commerce électronique qui influent directement sur le comportement des consommateurs en matière de prise de décision et de craintes en ligne. Nous élaborons une méthodologie pour mesurer avec précision le moment où surviennent la question de la confidentialité, les perceptions en ligne et les craintes de divulgation et de pertes financières. • Intégration de personnalisation, contrôle et paiement conditionnel : nous proposons une nouvelle plateforme de paiement en ligne qui supporte à la fois la personnalisation et les paiements multiples et conditionnels, tout en préservant la vie privée du détenteur de carte. • Exploration de l’interaction des usagers en ligne versus la sensibilisation à la cybersécurité : nous relatons une expérience de magasinage en ligne qui met en relief la perception du risque de cybercriminalité dans les activités en ligne et le comportement des utilisateurs lié à leur préoccupation en matière de confidentialité. • Équilibre entre utilité des données et vie privée : nous proposons un modèle de préservation de vie privée basé sur l’algorithme « k-means » et sur le modèle « k-coRating » afin de soutenir l’utilité des données dans les recommandations en ligne tout en préservant la vie privée des usagers. • Métrique de stabilité des préférences des utilisateurs : nous ciblons une meilleure méthode de recommandation qui respecte le changement des préférences des usagers par l’intermédiaire d’un réseau neural. Ce qui constitue une amélioration à la fois efficace et performante pour les systèmes de recommandation. Cette thèse porte essentiellement sur quatre aspects majeurs liés : 1) aux plateformes des paiements en ligne, 2) au comportement de l’usager dans les transactions de paiement en ligne (prise de décision, multi-craintes, cybersécurité, perception du risque), 3) à la stabilité de ses préférences dans les recommandations en ligne, 4) à l’équilibre entre vie privée et utilité des données en ligne pour les systèmes de recommandation. / Technologies in Human-Machine Interaction (HMI) are playing a vital role across the entire production process to design and deliver advanced digital systems. Given the exponential development of research in this field, two concepts are largely addressed to increase performance and efficiency of online environments: trust and user behavior. These two extents continue to proliferate in most designed solutions and are increasingly enriched by continuous investments in online payments and recommender systems. Along with the trend of digitalization, the objective of this research is to gain a better understanding of the various challenges in these two areas, make improvements and propose solutions more convenient to the users in terms of online perception and user behavior. In addition to the state of the art and challenges, this work is divided into five main parts, each one contributes to better enrich the online user experience in both online payments and system recommendations: • Online customer fears: We analyze different components of the website that may affect customer behavior in decision-making and online fears. We focus on customer perceptions regarding privacy violations and financial loss. We examine the influence on trust and payment security perception as well as their joint effect on three fundamentally important customers’ aspects: confidentiality, privacy concerns and financial fear perception. • Personalization, control and conditional payment: we propose a new online payment platform that supports both personalization and conditional multi-payments, while preserving the privacy of the cardholder. • Exploring user behavior and cybersecurity knowledge: we design a new website to conduct an experimental study in online shopping. The results highlight the impact of user’s perception in cybersecurity and privacy concerns on his online behavior when dealing with shopping activities. • Balance between data utility and user privacy: we propose a privacy-preserving method based on the “k-means” algorithm and the “k-coRating” model to support the utility of data in online recommendations while preserving user’s privacy. • User interest constancy metric: we propose a neural network to predict the user’s interests in recommender systems. Our aim is to provide an efficient method that respects the constancy and variations in user preferences. In this thesis, we focus on four major contributions related to: 1) online payment platforms, 2) user behavior in online payments regarding decision making, multi-fears and cyber security 3) user interest constancy in online recommendations, 4) balance between privacy and utility of online data in recommender systems.

《電子支付機構管理條例》自2015年2月實施後，陸續有相關子法作為補充。2015年底，金管會目標台灣非現金支付要在5年內達到52%，因此2016年被稱為｢支付元年｣。推廣線上支付最重要的除了市場動向外，莫過於法規的設置，因此本文探討目前的法制是否足以因應如此新興產業的需求，從進入門檻監理、消費者保護與產業發展三大個面向討論現行法規，並剖析是否有檢討之處。 由法制面審視我國對支付產業進入門檻的規定，反映了產業的競爭與發展的機會。而消費者的使用經驗是支付產業最佳的廣告，尤其支付系統多由小額且龐雜的交易組成，一旦紛爭發生，使用者大多自認倒楣，因此具有完備的防止糾紛或詐騙機制、資訊安全規範，產業才能永續發展。 / Since the implementation of the《Law on the Administration of Electronic Payment Institutions》in February 2015, the related regulations have been supplemented one after another. By the end of 2015, Financial Supervisory Commission set the target for non-cash payments in Taiwan to reach 52% of the total transaction within 5 years. So 2016 is called "the first year of payment". The most important thing promoting online payment is not only market trends, but also the establishment of legal system. Therefore, this article examines whether the current legal system is sufficient to meet the needs of such emerging industries, From entry barriers and supervision, consumer protection, industrial development, the three-oriented discussion of existing laws and regulations. From the legal point of view of Taiwanese payment industry entry barriers, it reflects the competition and development opportunities. The consumer experience is the best advertisement of payment industry. Especially the payment system is composed of small amount and complex transactions, once the dispute occurs, most users claim to be unfortunate. So there is a comprehensive mechanism to prevent disputes or fraud, information security norms, industry will be sustainable.