Andreu Pere Isern-Deyà

A Secure Automatic Fare Collection System for Time-based or Distance-based Services with Revocable Anonymity for Users

Automatic Fare Collection (AFC) systems calculate the fare that the users must pay depending on the time of service (time-based) or the points of entrance and exit of the system (distance-based). The progressive introduction of Information and Communication Technologies (ICT) allows the use of electronic tickets, which helps to reduce costs and improve the control of the infrastructures. Nevertheless, these systems must be secure against possible fraud and they must also preserve users’ privacy. Therefore, we have studied the security requirements for the timebased and distance-based systems and we have proposed a protocol for each of the AFC systems. The protocols offer strong privacy for honest users, i.e., the service provider is not able to disclose the identity of its users and, moreover, different journeys of the same user are not linkable between them. However, anonymity for users could be revoked if they misbehave. The protocols have been implemented in the Android mobile platform and its performance has been evaluated in two Android smartphones. The results remark that protocols are suitable to be used on AFC system with a medium class mobile device although they offer a better experience with a high-class smartphone. The appearance in the market of more powerful mobile devices suggests a better usability of our proposal in a near future.

On the practicability of using group signatures on mobile devices: implementation and performance analysis on the android platform

A group signature is a convenient cryptographic primitive to tackle with authentication and privacy problems. In the literature, it is used as an underlying black box by several theoretical proposals of secure applications and services, such as e-cash schemes, automatic fare collection systems and so on. However, there is a lack of implementations of group signature proposals to test their applied efficiency instead of purely show their mathematical complexity analysis. In this paper, we present, to the best of our knowledge, the first complete implementation and performance analysis of two group signature schemes on mobile devices: the pairing-based group signature due to Boneh et al. (referenced as BBS scheme) and the state-of-the-art non-pairing group signature by Ateniese et al. (called ACJT scheme). We test both implementations and we analyze their performance on a conventional laptop and two Android smartphones, comparing the gathered results to provide some interesting insights about which security parameter configurations perform better. This implementation expects to be useful so as to gain practice to know which is the real impact of using group signatures to the performance of applications, especially those used on mobile devices.

Untraceable, anonymous and fair micropayment scheme

The development of new applications of electronic commerce (e-commerce) that require the payment of small amounts of money to purchase services or goods opens new challenges in the security and privacy fields. This kind of payments are called micropayments and they have to provide a tradeoff between efficiency and security requirements to pay low-value items. In this paper we present a new efficient and secure micropayment scheme which fulfils the security properties that guarantee no financial risk for merchants and the privacy of the customers. In addition, the proposed system defines a fair exchange between the micropayment and the desired good or service. In this fair exchange, the anonymity and untraceability of the customers are assured. Finally, customers can request a refund whether they are no more interested on the services offered by merchants.

Applying Data Mining Techniques to Stock Market Analysis

The stock market can be viewed as a particular data mining and artificial intelligence problem. The movement in the stock exchange depends on capital gains and losses and most people consider the stock market erratic and unpredictable. However, patterns that allow the prediction of some movements can be found. Stock market analysis deals with the study of these patterns. It uses different techniques and strategies, mostly automatic that trigger buying and selling orders depending on different decision making algorithms. It can be considered as an intelligent treatment of past and present financial data in order to predict the stock market future behavior. Therefore it can be viewed as an artificial intelligence problem in the data mining field. This paper aims to study, construct and evaluate these investment strategies in order to predict future stock exchanges. Firstly, data mining techniques will be used to evaluate past stock prices and acquire useful knowledge through the calculation of some financial indicators. Next artificial intelligence strategies will be used to construct decision making trees.

Anonymous and Fair Micropayment Scheme with Protection against Coupon Theft

The development of new applications of electronic commerce (e-commerce) that require the payment of small amounts of money to purchase services or goods opens new challenges in the security and privacy fields. These payments are called micropayments and they provide a trade-off between efficiency and security requirements to pay low-value items. It is usual to assume low value fraud to achieve efficiency in micropayment systems. In this paper the authors present an improved version of an efficient and secure micropayment scheme which fulfils the security properties that guarantee no financial risk for merchants and the privacy of the customers. In addition, the proposed system defines a fair exchange between the coin and the desired good or service. In this fair exchange, the anonymity and untraceability of the customers are assured. Moreover, customers can request a refund whether they are no more interested on the services offered by merchants. As a novelty, an improvement of the scheme avoids customers to fraudulently use a refund operation to gain a little amount of money (called coupon). Thus, a new resolution subprotocol allows the merchant to avoid the loss of any single coupon.

A Secure Multicoupon Solution for Multi-merchant Scenarios

Electronic multicoupons are the equivalent of paper-based coupons booklets, offered to customers in order to achieve discounts or gifts from one or more merchants for goods or services. To date, most of the previous proposals have focused in scenarios where multiple customers can interact with a single merchant. But this restriction is a serious drawback for the expansion of the use of electronic coupons, since each customer needs a preestablished relationship with each merchant. In this paper, we propose a new multicoupon scheme for multi-merchant scenarios, preserving security properties of previous single merchant schemes, but enhancing the efficiency and the security of the few solutions that deal with multi-merchant scenarios.

Decision trees in stock market analysis: construction and validation

Data Mining techniques and Artificial Intelligence strategies can be used to solve problems in the stock market field. Most people consider the stock market erratic and unpredictable since the movement in the stock exchange depends on capital gains and losses. Nevertheless, patterns that allow the prediction of some movements can be found and studied. In this sense, stock market analysis uses different automatic techniques and strategies that trigger buying and selling orders depending on different decision making algorithms. In this paper different investment strategies that predict future stock exchanges are studied and evaluated. Firstly, data mining approaches are used to evaluate past stock prices and acquire useful knowledge through the calculation of financial indicators. Transformed data are then classified using decision trees obtained through the application of Artificial Intelligence strategies. Finally, the different decision trees are analyzed and evaluated, showing accuracy rates and emphasizing total profit associated to capital gains.

MC-2D: An Efficient and Scalable Multicoupon Scheme

Electronic multicoupons are the digital version of paper-based booklet of coupons, which allow a customer to obtain goods or services from a merchant typically with discounts or gifts. In this paper, we propose a multicoupon scheme for multi-merchant environments that enhances the security and the efficiency as regards the previous solution that deals with this kind of scenario. On one hand, our scheme meets basic security requirements (unforgeability, reuse detection), but also unsplittability. This fact will help to increase the trust on the part of merchants. On the other hand, we focus on achieving a high degree of privacy for customers (anonymity, unlinkability, confidentiality) that will contribute to gaining the trust of the involved customers. Moreover, we provide measures to protect honest parties from dishonest participants, keeping in mind the scalability and efficiency of the multicoupon scheme, to attract customers and merchants. In addition, we show by implementation that our proposal outperforms previous solutions of this kind.

Privacy on Mobile Coupons Booklets

Electronic coupons booklets are the equivalent of paper-based coupons booklets, offered to customers as a great opportunity to obtain a better offer from merchants. In this book chapter, the authors describe the main coupons booklet scenarios and identify the basic and additional security requirements. They review the state-of-the-art of the coupons booklet solutions and discuss about the main challenges: security, privacy and efficiency. In order to solve all these challenges, they present a coupons booklet scheme for the mobile scenario. They analyze their proposal to prove it meets all security and privacy requirements, and provide some performance results to prove it is a viable solution.

Anonymous, Secure and Fair Micropayment System to Access Location-Based Services

Some Internet service providers establish a fare for each access to the service. Micropayments are useful for the payment of low value services. One kind of service that can be benefited from the micropayment is the group of services based on location. Brand new mobile devices are capable to access data networks and also they can execute complex applications. Furthermore, these devices implement location systems like GPS. The combination of both capabilities can be useful to build new ubiquitous applications based on user location. These applications provide valuable information related to their location to the customers of the service.