Solving identity delegation problem in the e-government environment

At present, many countries allow citizens or entities to interact with the government outside the telematic environment through a legal representative who is granted powers of representation. However, if the interaction takes place through the Internet, only primitive mechanisms of representation are available, and these are mainly based on non-dynamic offline processes that do not enable quick and easy identity delegation. This paper proposes a system of dynamic delegation of identity between two generic entities that can solve the problem of delegated access to the telematic services provided by public authorities. The solution herein is based on the generation of a delegation token created from a proxy certificate that allows the delegating entity to delegate identity to another on the basis of a subset of its attributes as delegator, while also establishing in the delegation token itself restrictions on the services accessible to the delegated entity and the validity period of delegation. Further, the paper presents the mechanisms needed to either revoke a delegation token or to check whether a delegation token has been revoked. Implications for theory and practice and suggestions for future research are discussed.

Contribución al estudio del criptoanálisis y diseño de los criptosistemas caóticos

The extraordinary increase of new information technologies, the development of Internet, the electronic commerce, the e-government, mobile telephony and future cloud computing and storage, have provided great benefits in all areas of society. Besides these, there are new challenges for the protection of information, such as the loss of confidentiality and integrity of electronic documents. Cryptography plays a key role by providing the necessary tools to ensure the safety of these new media. It is imperative to intensify the research in this area, to meet the growing demand for new secure cryptographic techniques. The theory of chaotic nonlinear dynamical systems and the theory of cryptography give rise to the chaotic cryptography, which is the field of study of this thesis. The link between cryptography and chaotic systems is still subject of intense study. The combination of apparently stochastic behavior, the properties of sensitivity to initial conditions and parameters, ergodicity, mixing, and the fact that periodic points are dense, suggests that chaotic orbits resemble random sequences. This fact, and the ability to synchronize multiple chaotic systems, initially described by Pecora and Carroll, has generated an avalanche of research papers that relate cryptography and chaos. The chaotic cryptography addresses two fundamental design paradigms. In the first paradigm, chaotic cryptosystems are designed using continuous time, mainly based on chaotic synchronization techniques; they are implemented with analog circuits or by computer simulation. In the second paradigm, chaotic cryptosystems are constructed using discrete time and generally do not depend on chaos synchronization techniques. The contributions in this thesis involve three aspects about chaotic cryptography. The first one is a theoretical analysis of the geometric properties of some of the most employed chaotic attractors for the design of chaotic cryptosystems. The second one is the cryptanalysis of continuos chaotic cryptosystems and finally concludes with three new designs of cryptographically secure chaotic pseudorandom generators. The main accomplishments contained in this thesis are: v Development of a method for determining the parameters of some double scroll chaotic systems, including Lorenz system and Chua’s circuit. First, some geometrical characteristics of chaotic system have been used to reduce the search space of parameters. Next, a scheme based on the synchronization of chaotic systems was built. The geometric properties have been employed as matching criterion, to determine the values of the parameters with the desired accuracy. The method is not affected by a moderate amount of noise in the waveform. The proposed method has been applied to find security flaws in the continuous chaotic encryption systems. Based on previous results, the chaotic ciphers proposed by Wang and Bu and those proposed by Xu and Li are cryptanalyzed. We propose some solutions to improve the cryptosystems, although very limited because these systems are not suitable for use in cryptography. Development of a method for determining the parameters of the Lorenz system, when it is used in the design of two-channel cryptosystem. The method uses the geometric properties of the Lorenz system. The search space of parameters has been reduced. Next, the parameters have been accurately determined from the ciphertext. The method has been applied to cryptanalysis of an encryption scheme proposed by Jiang. In 2005, Gunay et al. proposed a chaotic encryption system based on a cellular neural network implementation of Chua’s circuit. This scheme has been cryptanalyzed. Some gaps in security design have been identified. Based on the theoretical results of digital chaotic systems and cryptanalysis of several chaotic ciphers recently proposed, a family of pseudorandom generators has been designed using finite precision. The design is based on the coupling of several piecewise linear chaotic maps. Based on the above results a new family of chaotic pseudorandom generators named Trident has been designed. These generators have been specially designed to meet the needs of real-time encryption of mobile technology. According to the above results, this thesis proposes another family of pseudorandom generators called Trifork. These generators are based on a combination of perturbed Lagged Fibonacci generators. This family of generators is cryptographically secure and suitable for use in real-time encryption. Detailed analysis shows that the proposed pseudorandom generator can provide fast encryption speed and a high level of security, at the same time. El extraordinario auge de las nuevas tecnologías de la información, el desarrollo de Internet, el comercio electrónico, la administración electrónica, la telefonía móvil y la futura computación y almacenamiento en la nube, han proporcionado grandes beneficios en todos los ámbitos de la sociedad. Junto a éstos, se presentan nuevos retos para la protección de la información, como la suplantación de personalidad y la pérdida de la confidencialidad e integridad de los documentos electrónicos. La criptografía juega un papel fundamental aportando las herramientas necesarias para garantizar la seguridad de estos nuevos medios, pero es imperativo intensificar la investigación en este ámbito para dar respuesta a la demanda creciente de nuevas técnicas criptográficas seguras. La teoría de los sistemas dinámicos no lineales junto a la criptografía dan lugar a la ((criptografía caótica)), que es el campo de estudio de esta tesis. El vínculo entre la criptografía y los sistemas caóticos continúa siendo objeto de un intenso estudio. La combinación del comportamiento aparentemente estocástico, las propiedades de sensibilidad a las condiciones iniciales y a los parámetros, la ergodicidad, la mezcla, y que los puntos periódicos sean densos asemejan las órbitas caóticas a secuencias aleatorias, lo que supone su potencial utilización en el enmascaramiento de mensajes. Este hecho, junto a la posibilidad de sincronizar varios sistemas caóticos descrita inicialmente en los trabajos de Pecora y Carroll, ha generado una avalancha de trabajos de investigación donde se plantean muchas ideas sobre la forma de realizar sistemas de comunicaciones seguros, relacionando así la criptografía y el caos. La criptografía caótica aborda dos paradigmas de diseño fundamentales. En el primero, los criptosistemas caóticos se diseñan utilizando circuitos analógicos, principalmente basados en las técnicas de sincronización caótica; en el segundo, los criptosistemas caóticos se construyen en circuitos discretos u ordenadores, y generalmente no dependen de las técnicas de sincronización del caos. Nuestra contribución en esta tesis implica tres aspectos sobre el cifrado caótico. En primer lugar, se realiza un análisis teórico de las propiedades geométricas de algunos de los sistemas caóticos más empleados en el diseño de criptosistemas caóticos vii continuos; en segundo lugar, se realiza el criptoanálisis de cifrados caóticos continuos basados en el análisis anterior; y, finalmente, se realizan tres nuevas propuestas de diseño de generadores de secuencias pseudoaleatorias criptográficamente seguros y rápidos. La primera parte de esta memoria realiza un análisis crítico acerca de la seguridad de los criptosistemas caóticos, llegando a la conclusión de que la gran mayoría de los algoritmos de cifrado caóticos continuos —ya sean realizados físicamente o programados numéricamente— tienen serios inconvenientes para proteger la confidencialidad de la información ya que son inseguros e ineficientes. Asimismo una gran parte de los criptosistemas caóticos discretos propuestos se consideran inseguros y otros no han sido atacados por lo que se considera necesario más trabajo de criptoanálisis. Esta parte concluye señalando las principales debilidades encontradas en los criptosistemas analizados y algunas recomendaciones para su mejora. En la segunda parte se diseña un método de criptoanálisis que permite la identificaci ón de los parámetros, que en general forman parte de la clave, de algoritmos de cifrado basados en sistemas caóticos de Lorenz y similares, que utilizan los esquemas de sincronización excitador-respuesta. Este método se basa en algunas características geométricas del atractor de Lorenz. El método diseñado se ha empleado para criptoanalizar eficientemente tres algoritmos de cifrado. Finalmente se realiza el criptoanálisis de otros dos esquemas de cifrado propuestos recientemente. La tercera parte de la tesis abarca el diseño de generadores de secuencias pseudoaleatorias criptográficamente seguras, basadas en aplicaciones caóticas, realizando las pruebas estadísticas, que corroboran las propiedades de aleatoriedad. Estos generadores pueden ser utilizados en el desarrollo de sistemas de cifrado en flujo y para cubrir las necesidades del cifrado en tiempo real. Una cuestión importante en el diseño de sistemas de cifrado discreto caótico es la degradación dinámica debida a la precisión finita; sin embargo, la mayoría de los diseñadores de sistemas de cifrado discreto caótico no ha considerado seriamente este aspecto. En esta tesis se hace hincapié en la importancia de esta cuestión y se contribuye a su esclarecimiento con algunas consideraciones iniciales. Ya que las cuestiones teóricas sobre la dinámica de la degradación de los sistemas caóticos digitales no ha sido totalmente resuelta, en este trabajo utilizamos algunas soluciones prácticas para evitar esta dificultad teórica. Entre las técnicas posibles, se proponen y evalúan varias soluciones, como operaciones de rotación de bits y desplazamiento de bits, que combinadas con la variación dinámica de parámetros y con la perturbación cruzada, proporcionan un excelente remedio al problema de la degradación dinámica. Además de los problemas de seguridad sobre la degradación dinámica, muchos criptosistemas se rompen debido a su diseño descuidado, no a causa de los defectos esenciales de los sistemas caóticos digitales. Este hecho se ha tomado en cuenta en esta tesis y se ha logrado el diseño de generadores pseudoaleatorios caóticos criptogr áficamente seguros.

New methodology for the integration of biometric features in speaker recognition systems applied to security environments

La cuestión principal abordada en esta tesis doctoral es la mejora de los sistemas biométricos de reconocimiento de personas a partir de la voz, proponiendo el uso de una nueva parametrización, que hemos denominado parametrización biométrica extendida dependiente de género (GDEBP en sus siglas en inglés). No se propone una ruptura completa respecto a los parámetros clásicos sino una nueva forma de utilizarlos y complementarlos. En concreto, proponemos el uso de parámetros diferentes dependiendo del género del locutor, ya que como es bien sabido, la voz masculina y femenina presentan características diferentes que deberán modelarse, por tanto, de diferente manera. Además complementamos los parámetros clásicos utilizados (MFFC extraídos de la señal de voz), con un nuevo conjunto de parámetros extraídos a partir de la deconstrucción de la señal de voz en sus componentes de fuente glótica (más relacionada con el proceso y órganos de fonación y por tanto con características físicas del locutor) y de tracto vocal (más relacionada con la articulación acústica y por tanto con el mensaje emitido). Para verificar la validez de esta propuesta se plantean diversos escenarios, utilizando diferentes bases de datos, para validar que la GDEBP permite generar una descripción más precisa de los locutores que los parámetros MFCC clásicos independientes del género. En concreto se plantean diferentes escenarios de identificación sobre texto restringido y texto independiente utilizando las bases de datos de HESPERIA y ALBAYZIN. El trabajo también se completa con la participación en dos competiciones internacionales de reconocimiento de locutor, NIST SRE (2010 y 2012) y MOBIO 2013. En el primer caso debido a la naturaleza de las bases de datos utilizadas se obtuvieron resultados cercanos al estado del arte, mientras que en el segundo de los casos el sistema presentado obtuvo la mejor tasa de reconocimiento para locutores femeninos. A pesar de que el objetivo principal de esta tesis no es el estudio de sistemas de clasificación, sí ha sido necesario analizar el rendimiento de diferentes sistemas de clasificación, para ver el rendimiento de la parametrización propuesta. En concreto, se ha abordado el uso de sistemas de reconocimiento basados en el paradigma GMM-UBM, supervectores e i-vectors. Los resultados que se presentan confirman que la utilización de características que permitan describir los locutores de manera más precisa es en cierto modo más importante que la elección del sistema de clasificación utilizado por el sistema. En este sentido la parametrización propuesta supone un paso adelante en la mejora de los sistemas de reconocimiento biométrico de personas por la voz, ya que incluso con sistemas de clasificación relativamente simples se consiguen tasas de reconocimiento realmente competitivas. ABSTRACT The main question addressed in this thesis is the improvement of automatic speaker recognition systems, by the introduction of a new front-end module that we have called Gender Dependent Extended Biometric Parameterisation (GDEBP). This front-end do not constitute a complete break with respect to classical parameterisation techniques used in speaker recognition but a new way to obtain these parameters while introducing some complementary ones. Specifically, we propose a gender-dependent parameterisation, since as it is well known male and female voices have different characteristic, and therefore the use of different parameters to model these distinguishing characteristics should provide a better characterisation of speakers. Additionally, we propose the introduction of a new set of biometric parameters extracted from the components which result from the deconstruction of the voice into its glottal source estimate (close related to the phonation process and the involved organs, and therefore the physical characteristics of the speaker) and vocal tract estimate (close related to acoustic articulation and therefore to the spoken message). These biometric parameters constitute a complement to the classical MFCC extracted from the power spectral density of speech as a whole. In order to check the validity of this proposal we establish different practical scenarios, using different databases, so we can conclude that a GDEBP generates a more accurate description of speakers than classical approaches based on gender-independent MFCC. Specifically, we propose scenarios based on text-constrain and text-independent test using HESPERIA and ALBAYZIN databases. This work is also completed with the participation in two international speaker recognition evaluations: NIST SRE (2010 and 2012) and MOBIO 2013, with diverse results. In the first case, due to the nature of the NIST databases, we obtain results closed to state-of-the-art although confirming our hypothesis, whereas in the MOBIO SRE we obtain the best simple system performance for female speakers. Although the study of classification systems is beyond the scope of this thesis, we found it necessary to analise the performance of different classification systems, in order to verify the effect of them on the propose parameterisation. In particular, we have addressed the use of speaker recognition systems based on the GMM-UBM paradigm, supervectors and i-vectors. The presented results confirm that the selection of a set of parameters that allows for a more accurate description of the speakers is as important as the selection of the classification method used by the biometric system. In this sense, the proposed parameterisation constitutes a step forward in improving speaker recognition systems, since even when using relatively simple classification systems, really competitive recognition rates are achieved.

Autonomous classification models in ubiquitous environments

Stream-mining approach is defined as a set of cutting-edge techniques designed to process streams of data in real time, in order to extract knowledge. In the particular case of classification, stream-mining has to adapt its behaviour to the volatile underlying data distributions, what has been called concept drift. Moreover, it is important to note that concept drift may lead to situations where predictive models become invalid and have therefore to be updated to represent the actual concepts that data poses. In this context, there is a specific type of concept drift, known as recurrent concept drift, where the concepts represented by data have already appeared in the past. In those cases the learning process could be saved or at least minimized by applying a previously trained model. This could be extremely useful in ubiquitous environments that are characterized by the existence of resource constrained devices. To deal with the aforementioned scenario, meta-models can be used in the process of enhancing the drift detection mechanisms used by data stream algorithms, by representing and predicting when the change will occur. There are some real-world situations where a concept reappears, as in the case of intrusion detection systems (IDS), where the same incidents or an adaptation of them usually reappear over time. In these environments the early prediction of drift by means of a better knowledge of past models can help to anticipate to the change, thus improving efficiency of the model regarding the training instances needed. By means of using meta-models as a recurrent drift detection mechanism, the ability to share concepts representations among different data mining processes is open. That kind of exchanges could improve the accuracy of the resultant local model as such model may benefit from patterns similar to the local concept that were observed in other scenarios, but not yet locally. This would also improve the efficiency of training instances used during the classification process, as long as the exchange of models would aid in the application of already trained recurrent models, that have been previously seen by any of the collaborative devices. Which it is to say that the scope of recurrence detection and representation is broaden. In fact the detection, representation and exchange of concept drift patterns would be extremely useful for the law enforcement activities fighting against cyber crime. Being the information exchange one of the main pillars of cooperation, national units would benefit from the experience and knowledge gained by third parties. Moreover, in the specific scope of critical infrastructures protection it is crucial to count with information exchange mechanisms, both from a strategical and technical scope. The exchange of concept drift detection schemes in cyber security environments would aid in the process of preventing, detecting and effectively responding to threads in cyber space. Furthermore, as a complement of meta-models, a mechanism to assess the similarity between classification models is also needed when dealing with recurrent concepts. In this context, when reusing a previously trained model a rough comparison between concepts is usually made, applying boolean logic. The introduction of fuzzy logic comparisons between models could lead to a better efficient reuse of previously seen concepts, by applying not just equal models, but also similar ones. This work faces the aforementioned open issues by means of: the MMPRec system, that integrates a meta-model mechanism and a fuzzy similarity function; a collaborative environment to share meta-models between different devices; a recurrent drift generator that allows to test the usefulness of recurrent drift systems, as it is the case of MMPRec. Moreover, this thesis presents an experimental validation of the proposed contributions using synthetic and real datasets.