Cryptographic techniques used to provide integrity of digital content in long-term storage

The main objective of the project was to obtain advanced mathematical methods to guarantee the verification that a required level of data integrity is maintained in long-term storage. The secondary objective was to provide methods for the evaluation of data loss and recovery. Additionally, we have provided the following initial constraints for the problem: a limitation of additional storage space, a minimal threshold for desired level of data integrity and a defined probability of a single-bit corruption. With regard to the main objective, the study group focused on the exploration methods based on hash values. It has been indicated that in the case of tight constraints, suggested by PWPW, it is not possible to provide any method based only on the hash values. This observation stems from the fact that the high probability of bit corruption leads to unacceptably large number of broken hashes, which in turn stands in contradiction with the limitation for additional storage space. However, having loosened the initial constraints to some extent, the study group has proposed two methods that use only the hash values. The first method, based on a simple scheme of data subdivision in disjoint subsets, has been provided as a benchmark for other methods discussed in this report. The second method ("hypercube" method), introduced as a type of the wider class of clever-subdivision methods, is built on the concept of rewriting data-stream into a n-dimensional hypercube and calculating hash values for some particular (overlapping) sections of the cube. We have obtained interesting results by combining hash value methods with error-correction techniques. The proposed framework, based on the BCH codes, appears to have promising properties, hence further research in this field is strongly recommended. As a part of the report we have also presented features of secret sharing methods for the benefit of novel distributed data-storage scenarios. We have provided an overview of some interesting aspects of secret sharing techniques and several examples of possible applications

Applications of graph theory to wireless networks and opinion analysis

La teoría de grafos es una rama importante dentro de la matemática discreta. Su uso ha aumentado recientemente dada la conveniencia de los grafos para estructurar datos, para analizarlos y para generarlos a través de modelos. El objetivo de esta tesis es aplicar teoría de grafos a la optimización de redes inalámbricas y al análisis de opinión. El primer conjunto de contribuciones de esta tesis versa sobre la aplicación de teoría de grafos a redes inalámbricas. El rendimiento de estas redes depende de la correcta distribución de canales de frecuencia en un espacio compartido. Para optimizar estas redes se proponen diferentes técnicas, desde la aplicación de heurísticas como simulated annealing a la negociación automática. Cualquiera de estas técnicas requiere un modelo teórico de la red inalámbrica en cuestión. Nuestro modelo de redes Wi-Fi utiliza grafos geométricos para este propósito. Los vértices representan los dispositivos de la red, sean clientes o puntos de acceso, mientras que las aristas representan las señales entre dichos dispositivos. Estos grafos son de tipo geométrico, por lo que los vértices tienen posición en el espacio, y las aristas tienen longitud. Con esta estructura y la aplicación de un modelo de propagación y de uso, podemos simular redes inalámbricas y contribuir a su optimización. Usando dicho modelo basado en grafos, hemos estudiado el efecto de la interferencia cocanal en redes Wi-Fi 4 y mostramos una mejora de rendimiento asociada a la técnica de channel bonding cuando se usa en regiones donde hay por lo menos 13 canales disponibles. Por otra parte, en esta tesis doctoral hemos aplicado teoría de grafos al análisis de opinión dentro de la línea de investigación de SensoGraph, un método con el que se realiza un análisis de opinión sobre un conjunto de elementos usando grafos de proximidad, lo que permite manejar grandes conjuntos de datos. Además, hemos desarrollado un método de análisis de opinión que emplea la asignación manual de aristas y distancias en un grafo para estudiar la similaridad entre las muestras dos a dos. Adicionalmente, se han explorado otros temas sin relación con los grafos, pero que entran dentro de la aplicación de las matemáticas a un problema de la ingeniería telemática. Se ha desarrollado un sistema de votación electrónica basado en mixnets, secreto compartido de Shamir y cuerpos finitos. Dicha propuesta ofrece un sistema de verificación numérico novedoso a la vez que mantiene las propiedades esenciales de los sistemas de votación

Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others

Dagstuhl News January - December 2011

"Dagstuhl News" is a publication edited especially for the members of the Foundation "Informatikzentrum Schloss Dagstuhl" to thank them for their support. The News give a summary of the scientific work being done in Dagstuhl. Each Dagstuhl Seminar is presented by a small abstract describing the contents and scientific highlights of the seminar as well as the perspectives or challenges of the research topic

Applied Metaheuristic Computing

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC