Editorial: Special issue CISIS12-IGPL

The nine contributions selected in this special issue represent a collection of extended papers presented at the 5th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2012)

4th International Conference, CISIS 2011, Held at IWANN 2011, Torremolinos-Málaga, Spain, June 8-10, 2011. Proceedings

This book constitutes the refereed proceedings of the 4th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2011, held in Torremolinos-Málaga, in June 2011 as a satellite event of IWANN 2011, the International Work-Conference on Artificial and Natural Neural Networks. The 38 revised full papers presented were carefully reviewed and selected from a total of 70 submissions. The papers are organized in topical sections on machine learning and intelligence, network security, cryptography, securing software, and applications of intelligent methods for security

Proceedings of the International Workshop on Computational Intelligence in Security for Information Systems CISIS’08

The International Workshop on Computational Intelligence for Security in Information Systems (CISIS) proposes a meeting ground to the various communities involved in building intelligent systems for security, namely: information security, data mining, adaptive learning methods and soft computing among others. The main goal is to allow experts and researchers to assess the benefits of learning methods in the data-mining area for information-security applications. The Workshop offers the opportunity to interact with the leading industries actively involved in the critical area of security, and have a picture of the current solutions adopted in practical domains. This volume of Advances in Soft Computing contains accepted papers presented at CISIS’08, which was held in Genova, Italy, on October 23rd-24th, 2008. The selection process to set up the Workshop program yielded a collection of about 40 papers. This allowed the Scientific Committee to verify the vital and crucial nature of the topics involved in the event, and resulted in an acceptance rate of about 60% of the originally submitted manuscripts

Health Access Broker: Secure, Patient-Controlled Management of Personal Health Records in the Cloud

Secure and privacy-preserving management of Personal Health Records (PHRs) has proved to be a major challenge in modern healthcare. Current solutions generally do not offer patients a choice in where the data is actually stored and also rely on at least one fully trusted element that patients must also trust with their data. In this work, we present the Health Access Broker (HAB), a patient-controlled service for secure PHR sharing that (a) does not impose a specific storage location (uniquely for a PHR system), and (b) does not assume any of its components to be fully secure against adversarial threats. Instead, HAB introduces a novel auditing and intrusion-detection mechanism where its workflow is securely logged and continuously inspected to provide auditability of data access and quickly detect any intrusions.Comment: Copy of the paper accepted at 13th International Conference on Computational Intelligence in Security for Information Systems (CISIS

Salamanca, Spain, September 11th-13th, 2013 Proceedings

This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2013, CISIS 2013 and ICEUTE 2013, all conferences held in the beautiful and historic city of Salamanca (Spain), in September 2013. Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a through peer-review process, the 8th SOCO 2013 International Program Committee selected 40 papers which are published in these conference proceedings, and represents an acceptance rate of 41%. In this relevant edition a special emphasis was put on the organization of special sessions. Four special sessions were organized related to relevant topics as: Systems, Man, and Cybernetics, Data Mining for Industrial and Environmental Applications, Soft Computing Methods in Bioinformatics, and Soft Computing Methods, Modelling and Simulation in Electrical Engineer. The aim of the 6th CISIS 2013 conference is to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communities of Computational Intelligence, Information Security, and Data Mining. The need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, is intended to be the catalyst and the aggregation stimulus for the overall event. After a through peer-review process, the CISIS 2013 International Program Committee selected 23 papers which are published in these conference proceedings achieving an acceptance rate of 39%. In the case of 4th ICEUTE 2013, the International Program Committee selected 11 papers which are published in these conference proceedings. The selection of papers was extremely rigorous in order to maintain the high quality of the conference and we would like to thank the members of the Program Committees for their hard work in the reviewing process. This is a crucial process to the creation of a high standard conference and the SOCO, CISIS and ICEUTE conferences would not exist without their help

A collective intelligence approach for building student's trustworthiness profile in online learning

(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Information and communication technologies have been widely adopted in most of educational institutions to support e-Learning through different learning methodologies such as computer supported collaborative learning, which has become one of the most influencing learning paradigms. In this context, e-Learning stakeholders, are increasingly demanding new requirements, among them, information security is considered as a critical factor involved in on-line collaborative processes. Information security determines the accurate development of learning activities, especially when a group of students carries out on-line assessment, which conducts to grades or certificates, in these cases, IS is an essential issue that has to be considered. To date, even most advances security technological solutions have drawbacks that impede the development of overall security e-Learning frameworks. For this reason, this paper suggests enhancing technological security models with functional approaches, namely, we propose a functional security model based on trustworthiness and collective intelligence. Both of these topics are closely related to on-line collaborative learning and on-line assessment models. Therefore, the main goal of this paper is to discover how security can be enhanced with trustworthiness in an on-line collaborative learning scenario through the study of the collective intelligence processes that occur on on-line assessment activities. To this end, a peer-to-peer public student's profile model, based on trustworthiness is proposed, and the main collective intelligence processes involved in the collaborative on-line assessments activities, are presented.Peer ReviewedPostprint (author's final draft

An Advanced Technique for User Identification Using Partial Fingerprint

User identification is a very interesting and complex task. Invasive biometrics is based on traits uniqueness and immutability over time. In forensic field, fingerprints have always been considered an essential element for personal recognition. The traditional issue is focused on full fingerprint images matching. In this paper an advanced technique for personal recognition based on partial fingerprint is proposed. This system is based on fingerprint local analysis and micro-features, endpoints and bifurcations, extraction. The proposed approach starts from minutiae extraction from a partial fingerprint image and ends with the final matching score between fingerprint pairs. The computation of likelihood ratios in fingerprint identification is computed by trying every possible overlapping of the partial image with complete image. The first experimental results conducted on the PolyU (Hong Kong Polytechnic University) free database show an encouraging performance in terms of identification accuracy