Classificação de anomalias e redução de falsos positivos em sistemas de detecção de intrusão baseados em rede utilizando métodos de agrupamento

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Malware distributed collection and pre-classification system using honeypot technology

Malware has become a major threat in the last years due to the ease of spread through the Internet. Malware detection has become difficult with the use of compression, polymorphic methods and techniques to detect and disable security software. Those and other obfuscation techniques pose a problem for detection and classification schemes that analyze malware behavior. In this paper we propose a distributed architecture to improve malware collection using different honeypot technologies to increase the variety of malware collected. We also present a daemon tool developed to grab malware distributed through spam and a pre-classification technique that uses antivirus technology to separate malware in generic classes. © 2009 SPIE.

Sistema de coleta, análise e detecção de código malicioso baseado no sistema imunológico humano

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Detecção de eventos de segurança de redes por intermédio de técnicas estatísticas e associativas aplicadas a fluxos de dados

Pós-graduação em Ciência da Computação - IBILCE

Análise da estabilidade transitória via rede neural Art-Artmap fuzzy Euclidiana modificada com treinamento continuado

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An alternative genotyping method using dye-labeled universal primer to reduce unspecific amplifications

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Quantificação da resoluçao do sistema SPECT-CZT através do uso da função de transferência modulada (MTF)

Pós-graduação em Biologia Geral e Aplicada - IBB

Firewall Dinâmico: uma implementação cliente/servidor

Pós-graduação em Ciência da Computação - IBILCE

Gama Câmara CZT: alteração de paradigmas em aquisição de imagens de medicina nuclear

Nuclear medicine is a medical specialty related to imagery that deals with imaging techniques, diagnosis and therapy, allowing observing the physiological state of tissues noninvasively by marking the molecules participating of these physiological processes with radioactive isotopes, thus creating the called radionuclides. The image of a radionuclide is one of the most important applications of radioactivity in nuclear medicine. The equipment’s of nuclear medicine imaging use the principle of radiation detection, turning it into an electrical signal which, through specific algorithms, allows forming tomographic images that provide information about the functional status of organs. New detection systems have been developed for tomographic acquisitions using solid state detectors. These devices use crystals of cadmium zinc telluride (CdZnTe). Some of the advantages of this detector are a significant improvement of signal to noise ratio, the increased spectral and spatial resolution, which in sum, result in greater clarity of the images obtained, opening new perspectives for imaging protocols previously unattainable. In contrast, all other gamma-cameras equipped with vacuum tubes have remained relatively unchanged for nearly fifty years. In these gamma-cameras, the images are obtained using two steps significantly less efficient: the gamma rays are converted to light through a first device, and then the light is converted into an electrical signal through a second device. One of functions the Medical Physicist is related to the quality control of equipment. This control ensures that the information and images provided are true and thus credible to be used in medical reports. To perform this type of analysis the physicist must understand the performance characteristics and operation of all equipment of the department concerned; besides, in the absence of specific legislation, proposing...(Complete abstract click electronic access below)

Aplicação de conjugado de microesferas de poliestireno para preparo de RNA no diagnóstico da cinomose canina por RT-qPCR

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A comparison about evolutionary algorithms for optimum-path forest clustering optimization

In this paper we deal with the problem of boosting the Optimum-Path Forest (OPF) clustering approach using evolutionary-based optimization techniques. As the OPF classifier performs an exhaustive search to find out the size of sample's neighborhood that allows it to reach the minimum graph cut as a quality measure, we compared several optimization techniques that can obtain close graph cut values to the ones obtained by brute force. Experiments in two public datasets in the context of unsupervised network intrusion detection have showed the evolutionary optimization techniques can find suitable values for the neighborhood faster than the exhaustive search. Additionally, we have showed that it is not necessary to employ many agents for such task, since the neighborhood size is defined by discrete values, with constrain the set of possible solution to a few ones.

Detection and Identification of Abnormalities in Customer Consumptions in Power Distribution Systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Well-conditioned robust observer for detection of family systems components

A new concept of fault detection and isolation using robust observation for systems with random noises is presented. The method selects the parameters from components that may fault during the process and constructs well conditioned robust observers, considering sensors faults. To isolate component failures via robust observation, a bank of detection observers is constructed, where each observer is only sensitive to one specified component failure while robust to all other component failures.

Well-conditioned robust observer for detection of faulty systems components

A new concept of fault detection and isolation using robust observation for systems with random noises is presented. The method selects the parameters from components that may fault during the process and constructs well conditioned robust observers, considering sensors faults. To isolate component failures via robust observation, a bank of detection observers is constructed, where each observer is only sensitive to one specified component failure while robust to all other component failures.

Design of a state observer using decay rate LMI constraints for fault detection in mechanical systems

Nowadays, one of the most important concerns for many companies is to maintain the operation of their systems without sudden equipment break down. Because of this, new techniques for fault detection and location in mechanical systems subject to dynamic loads have been developed. This paper studies of the influence of the decay rate in the design of state observers using LMI for fault detection in mechanical systems. This influence is analyzed by the performance index proposed by Huh and Stein for the condition of a state observer. An example is presented to illustrate the methodology discussed.