Catálogo de publicaciones - libros

A significant number of mobile payment systems have been proposed in recent years, most of them based on a scenario where all the entities are directly connected one to another (formally called ”Full connectivity scenario”). Despite of the advantages that the aforementioned scenario offers to protocol’s designers, regarding design simplification and development of payment protocols without losing security capabilities, the full connectivity scenario does not consider those situations in which the client cannot directly communicate with the issuer (Kiosk Centric Model) or the merchant has no direct communication with the acquirer (Client Centric Model). In order to overcome this restriction and contribute to the progress of m-commerce, in this paper we propose an anonymous protocol that uses a digital signature scheme with message recovery using self-certified public keys that is suitable for both the Kiosk Centric Model and Client Centric Model. As a result, our proposal shows that m-commerce is possible in restrictive connectivity scenarios, achieving the same security capabilities than other protocols designed for mobile payment systems based on ”Full connectivity scenario”.

Today, a web transaction is typically protected by using SSL/TLS. SSL/TLS without compulsion for a client’s public key certificate, which is the typical usage, is not able to fulfill the security requirements for web transactions. The main remaining threats for this use are client authentication and non-repudiation. This paper presents a scheme to address SSL/TLS security holes, when it is used for web transaction security. The focus is only on transaction that is carried out by using credit/debit cards. The scheme uses wireless public key infrastructure (WPKI) in the client’s mobile phone to generate a digital signature for the client. Thus we obtain client authentication and non-repudiation. At the same time, no overhead is imposed on the client, there is no need for any change to the actual system when performing the transaction, and no connection, by using the mobile phone, is required to perform the transaction.

The problem of supporting privacy preservation of XML databases within very large publish-subscribe systems is rapidly gaining interest for both academic and industrial research. It becomes even more challenging when XML data are managed and delivered according to the P2P paradigm, since malicious accesses and unpredictable attacks could take advantage from the totally-decentralized and untrusted nature of P2P networks. In this paper, we propose ℓ, a distributed framework for very large publish-subscribe systems which supports () privacy-preserving fragmentation of XML documents stored in P2P XML databases, and () the creation of trusted groups of peers by means of “self-certifying” XPath links. Furthermore, we present algorithms for querying privacy-preserving XML fragments in both schema-aware and schema-less mode, which are common scenarios when P2P XML databases operate in very large publish-subscribe systems. Finally, we complete our analytical contributions with an experimental study showing the effectiveness of our proposed framework.

Usability analysis tools are indispensable for improving efficiency of electronic environments including web based portals and services. The article presents a novel behaviorally centered usability analysis framework. The framework has been applied to elucidation of usability characteristic of a large corporate intranet with an extensive knowledge worker user base. Knowledge workers had a significant tendency to form elemental and complex browsing patterns, utilized relatively narrow spectrum of available resources, and generally exhibited diminutive exploratory behavior.

The World Wide Web has become an important source of information for tourists planning their vacation. So, tourism recommender systems supporting users in their decision making process by suggesting suitable holiday destinations or travel packages based on user profiles are an area of vivid research. Since a picture paints a thousand words we have conducted an online survey revealing significant dependencies between tourism-related photographs and tourist types. The results of the survey are packaged in a Web-based tourist profiling tool. It is now possible to generate a user profile in an enjoyable way by simply selecting photos without enduring lengthy form-based self assessments.

This study examines the relationship between individual characteristics, product characteristics and media richness fit to explain the consumer channel preference. Based on prior research, hypotheses were tested with a sample of 749 consumers. The results show that the media richness fit moderates the degree of the relationship between the individual/product characteristics and the consumer channel preference. Thus, depending on the level of the media richness fit, the level of confidence in the channel, the attitude towards the channel, the experience level with the channel, the perceived risk vis-à-vis the channel, the perceived product complexity, the perceived product intangibility, and the consumer’s product involvement correlate differently with the consumer channel preference. Theoretical and managerial implications of the findings and avenues for future research are discussed.

E-commerce is the commercial transaction between and among organizations and individuals enabled by the digital technologies. Most recently, it is mainly referred to as the Internet-based electronic commerce. E-commerce provides many benefits for organisations to conduct business on the Internet. Since 1994, millions of companies have stepped into the digital world. However, due to the lack of knowledge and expertise of new technologies and many other reasons, the e-adoption rate for Small and Medium-sized Enterprises (SMEs) still lags behind. This paper investigates the e-adoption status for SMEs in the Bury area of Greater Manchester, UK. To conduct the research, a survey method is employed and questionnaires are distributed to local SMEs. The collected date is analysed and results are compared to the national statistics. Results show that the adoption rate of information and communication technology (ICT) and e-commerce in Bury is a step ahead of the UK in general.

Mobile and Pervasive applications have received considerable attention over the last few years, extending the application boundaries of modern information and communication technology. However, the successful adoption of such systems in an enterprise relies on a positive investment decision. As general managers and chief information officers (CIOs) still lack exhaustive experience with ubiquitous systems, there is a need to communicate this potential to this target group, guided by reliable corporate benefit arguments. This paper presents a set of simple taxonomies that help structuring and thereby communicating the nature and benefits of mobile and pervasive systems for corporate evaluation purposes. The taxonomies were validated involving a survey gathering the opinions of 20 CIOs. The taxonomy use is portrayed in a mobile logistics application case from the chemical industry.

In this paper, we propose a user interface for online shopping that uses a two dimensional product map to present products. This map is created using multidimensional scaling (MDS). Dissimilarities between products are computed using an adapted version of Gower’s coefficient of similarity based on the attributes of the product. The user can zoom in and out by drawing rectangles. We show an application of this user interface to MP3 players and give an interpretation of the product map.

The open nature of collaborative recommender systems present a security problem. Attackers that cannot be readily distinguished from ordinary users may inject biased profiles, degrading the objectivity and accuracy of the system over time. The standard user-based collaborative filtering algorithm has been shown quite vulnerable to such attacks. In this paper, we examine relevance measures that complement neighbor similarity and their influence on algorithm robustness. In particular, we consider two techniques, significance weighting and trust weighting, that attempt to calculate the utility of a neighbor with respect to rating prediction. Such techniques have been used to improve prediction accuracy in collaborative filtering. We show that significance weighting, in particular, also results in improved robustness under profile injection attacks.