Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The analysis of network traffic is a key area for the management of fault-tolerant systems, since anomalies in network traffic can affect the availability and quality of service (QoS). Intrusion detection systems in computer networks are used to analyze network traffic in order to detect attacks and anomalies. The analysis based on anomalies allows attacks detection by analyzing the behavior of the traffic network. This work proposes an intrusion detection tool to quickly and effectively detect anomalies in computer networks generated by denial of service (DoS). The detection algorithm is based on the two-dimensional wavelet transform (2D Wavelet), a derived method of signal analysis. The wavelet transform is a mathematical tool with low computational cost that explores the existing information present in the input samples according to the different levels of the transformation. The proposed algorithm detects anomalies directly based on the wavelet coefficients, considering threshold techniques. This operation does not require the reconstruction of the original signal. Experiments were performed using two databases: a synthetic (DARPA) and another one from data collected at the Federal University of Santa Maria (UFSM), allowing analysis of the intrusion detection tool under different scenarios. The wavelets considered for the tests were all from the orthonormal family of Daubechies: Haar (Db1), Db2, Db4 and Db8 (with 1, 2, 4 and 8 null vanishing moments respectively). For the DARPA database we obtained a detection rate up to 100% using the Daubechies wavelet transform Db4, considering normalized wavelet coefficients. For the database collected at UFSM the detection rate was 95%, again considering Db4 wavelet transform with normalized wavelet coefficients. / A análise de tráfego de rede é uma área fundamental no gerenciamento de sistemas tolerantes a falhas, pois anomalias no tráfego de rede podem afetar a disponibilidade e a qualidade do serviço (QoS). Sistemas detectores de intrusão em redes de computadores são utilizados para analisar o tráfego de rede com o objetivo de detectar ataques ou anomalias. A análise baseada em anomalias permite detectar ataques através da análise do comportamento do tráfego de rede. Este trabalho propõe uma ferramenta de detecção de intrusão rápida e eficaz para detectar anomalias em redes de computadores geradas por ataques de negação de serviço (DoS). O algoritmo de detecção é baseado na transformada Wavelet bidimensional (Wavelet 2D), um método derivado da análise de sinais. A transformada wavelet é uma ferramenta matemática de baixo custo computacional, que explora as informações presentes nas amostras de entrada ao longo dos diversos níveis da transformação. O algoritmo proposto detecta anomalias diretamente nos coeficientes wavelets através de técnicas de corte, não necessitando da reconstrução do sinal original. Foram realizados experimentos utilizando duas bases de dados: uma sintética (DARPA), e outra coletada na instituição de ensino (UFSM), permitindo a análise da ferramenta de detecção de intrusão sob diferentes cenários. As famílias wavelets utilizadas nos testes foram as wavelets ortonormais de Daubechies: Haar (Db1), Db2, Db4 e Db8 (com 1, 2, 4 e 8 momentos nulos respectivamente). Para a base de dados DARPA obteve-se uma taxa de detecção de ataques DoS de até 100% utilizando a wavelet de Daubechies Db4 com os coeficientes wavelets normalizados, e de 95% para a base de dados da UFSM com a wavelet de Daubechies Db4 com os coeficientes wavelets normalizados.

This thesis deals with method of blood vessels segmentation from retinal images acquired by fundus camera. There is explored possibility of using wavelet transform as fast outline segmentation. The thesis includes study problems of preprocessing input image and decomposition of image using 2D DWT. Furthermore there is explored possibility of parametrical images thresholding that ensue from application of 2D DWT. There are designed algorithms for cleaning off artifacts from rough vessel map of blood vessel structures. The realization of algorithm was solved in programming environment MATLAB. There was created a user control interface in graphic application GUIDE, for easy control of whole segmentation process. In conclusion of thesis is proceeded the discussion of segmentation results for images from DBME database and quantitative evaluation of results for DRIVE database images.

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