Abstract
The massive growth of the Internet and its services is currently being sustained by the mercantilization of users' identities and private data. Traditional services on the Web require the user to disclose many unnecessary sensitive identity attributes like bankcards, geographic position, or even personal health records in order to provide a service. In essence, the services are presented as free and constitute a means by which the user is mercantilized, often without realizing the real value of its data to the market. In this chapter the auhors describe OFELIA (Open Federated Environment for Leveraging of Identity and Authorization), a digital identity architecture designed from the ground up to be user centric. OFELIA is an identity/authorization versatile infrastructure that does not depend upon the massive aggregation of users' identity attributes to offer a highly versatile set of identity services but relies instead on having those attributes distributed among and protected by several otherwise unrelated Attribute Authorities. Only the end user, with his smartphone, knows how to aggregate these scattered Attribute Authorities' identity attributes back into some useful identifiable and authenticated entity identity that can then be used by Internet services in a secure and interoperable way.

Abstract
Since 2011, it's mandatory to prescribe through an electronic system in Portugal. Several third party companies start to develop prescribing software/interfaces that act as gateways to transmit the prescription data from the practitioners to the Health Ministry. The use of those companies in this circuit weakens the Prescription System's security levels and compromises the confidentiality and privacy of doctors and patients' personal data. Aim: The main aim is to propose a secure and safer Prescribing System that allows prescriptions' authentication and protects the patient data, keeping their identity confidential. Results: By protecting several system flaws, this proposed increases greatly the Prescription System security levels, protects patient data, and avoid its collection from Third Party Companies. Also the physical model of the electronic Prescription appears to have all the security and applicability requirements needed to function during a communication network dysfunction.

Abstract

Abstract
Determining the frequency of small subgraphs is an important computational task lying at the core of several graph mining methodologies, such as network motifs discovery or graphlet based measurements. In this paper we try to improve a class of algorithms available for this purpose, namely network-centric algorithms, which are based upon the enumeration of all sets of k connected nodes. Past approaches would essentially delay isomorphism tests until they had a finalized set of k nodes. In this paper we show how isomorphism testing can be done during the actual enumeration. We use a customized g-trie, a tree data structure, in order to encapsulate the topological information of the embedded subgraphs, identifying already known node permutations of the same subgraph type. With this we avoid redundancy and the need of an isomorphism test for each subgraph occurrence. We tested our algorithm, which we called FaSE, on a set of different real complex networks, both directed and undirected, showcasing that we indeed achieve significant speedups of at least one order of magnitude against past algorithms, paving the way for a faster network-centric approach.

Abstract
Recent studies of mobile Web trends show the continued explosion of mobile-friend content. However, the wide number and heterogeneity of mobile devices poses several challenges for Web programmers, who want automatic delivery of context and adaptation of the content to mobile devices. Hence, the device detection phase assumes an important role in this process. In this chapter, the authors compare the most used approaches for mobile device detection. Based on this study, they present an architecture for detecting and delivering uniform m-Learning content to students in a Higher School. The authors focus mainly on the XML device capabilities repository and on the REST API Web Service for dealing with device data. In the former, the authors detail the respective capabilities schema and present a new caching approach. In the latter, they present an extension of the current API for dealing with it. Finally, the authors validate their approach by presenting the overall data and statistics collected through the Google Analytics service, in order to better understand the adherence to the mobile Web interface, its evolution over time, and the main weaknesses. Copyright (C) 2013, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Abstract
Existent computer programming training environments help users to learn programming by solving problems from scratch. Nevertheless, initiating the resolution of a program can be frustrating and demotivating if the student does not know where and how to start. Skeleton programming facilitates a top-down design approach, where a partially functional system with complete highlevel structures is available, so the student needs only to progressively complete or update the code to meet the requirements of the problem. This paper presents CodeSkelGen - a program skeleton generator. CodeSkelGen generates skeleton or buggy Java programs from a complete annotated program solution provided by the teacher. The annotations are formally described within an annotation type and processed by an annotation processor. This processor is responsible for a set of actions ranging from the creation of dummy methods to the exchange of operator types included in the source code. The generator tool will be included in a learning environment that aims to assist teachers in the creation of programming exercises and to help students in their resolution. © Ricardo Queirós.