Segurança em redes sem fio: estudo sobre o desenvolvimento de conjuntos de dados para comparação de IDS

Pós-graduação em Engenharia Elétrica - FEIS

Correlação e visualização de alertas de segurança em redes de computadores

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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)

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

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Firewall Dinâmico: uma implementação cliente/servidor

Pós-graduação em Ciência da Computação - IBILCE

Detecção de intrusão em redes de computadores utilizando Floresta de Caminhos Ótimos

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.

O estabelecimento virtual na sociedade técnica: a necessária busca de segurança jurídica nas transações comerciais

Pós-graduação em Direito - FCHS

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

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Production grinding burn detection using acoustic emission and electric power signals

This work uses a monitoring system based on a PC platform, where the acoustic emission and electric power signals generated during the grinding process are used to investigate superficial burning occurrence in a surface grinding operation using two types of steel, three grinding conditions and an Al203 vitrified grinding wheel. Acoustic emission signals on the workpiece and grinding power were measured during a surface plunge operation until the grinding burn happened. From the results the standard deviation of the acoustic emission signal and the maximum electric power were calculated for each grinding pass. The proposed DPO parameter is the product between the power level and acoustic emission standard deviation. The results show that both signals can be used for burning detection, and the parameter DPO is the best indicator for the burning studied in this work. This can be explained by the high dispersion of the acoustic emission RMS level associated to the high power consumption when the grinding wheel lose its sharpness.

Diagnostic agreement of conventional and inverted scanned panoramic radiographs in the detection of the mandibular canal and the mental foramen.

The aim of this study was to evaluate the diagnostic agreement of conventional panoramic radiographs and their inverted scanned images in the detection of the mandibular canal and mental foramen. A total of 77 panoramic radiographs obtained from the files of totally edentulous patients were used. Digitization was done by means of a scanner with brightness and contrast adjustment, as well as image inversion. The extension of mandibular canal was divided into anterior, middle, and posterior regions, and the presence of a radiopaque line that characterized the mandibular canal was classified according to a 5-point confidence scale. The mental foramen was classified in 4 types: continuous, separated, diffuse, and unidentified. Both conventional and inverted scanned panoramic radiographs were evaluated by 3 calibrated implantologists at 2 distinct moments with a minimum interval of 10 days between them. Intraexaminer agreement was evaluated by Kappa statistics by point and by 95% confidence interval. Because the intraexaminer level of agreement was low, interexaminer agreements could not be carried out. The results showed a substantial (in 2 situations), moderate (in 16 situations), and fair (in 18 situations) intraexaminer agreement for mandibular canal and a substantial (in 1 situation), fair (in 1 situation), and moderate (in 10 situations) intraeaminer agreement for mental foramen. There were no statistically significant differences in most instances. In conclusion, the diagnostic agreement of conventional and inverted scanned panoramic radiographs for detection of mandibular canal and mental foramen was low.

Adaptative techniques for the human faces detection

This paper presents results from an efficient approach to an automatic detection and extraction of human faces from images with any color, texture or objects in background, that consist in find isosceles triangles formed by the eyes and mouth.

Transmission network expansion planning in full open market considering security constraints

This paper presents a mathematical model and a methodology to solve the transmission network expansion planning problem with security constraints in full competitive market, assuming that all generation programming plans present in the system operation are known. The methodology let us find an optimal transmission network expansion plan that allows the power system to operate adequately in each one of the generation programming plans specified in the full competitive market case, including a single contingency situation with generation rescheduling using the security (n-1) criterion. In this context, the centralized expansion planning with security constraints and the expansion planning in full competitive market are subsets of the proposal presented in this paper. The model provides a solution using a genetic algorithm designed to efficiently solve the reliable expansion planning in full competitive market. The results obtained for several known systems from the literature show the excellent performance of the proposed methodology.

Automatic system for thermal damage detection in manufacturing process with Internet monitoring

This work involved the development of a smart system dedicated to surface burning detection in the grinding process through constant monitoring of the process by acoustic emission and electrical power signals. A program in Visual Basic® for Windows® was developed, which collects the signals through an analog-digital converter and further processes them using burning detection algorithms already known. Three other parameters are proposed here and a comparative study carried out. When burning occurs, the newly developed software program sends a control signal warning the operator or interrupting the process, and delivers process information via the Internet. Parallel to this, the user can also interfere in the process via Internet, changing parameters and/or monitoring the grinding process. The findings of a comparative study of the various parameters are also discussed here. Copyright © 2006 by ABCM.

Wavelets and decision trees for target detection over sea surface using cosmo-skymed SAR data

We are investigating the combination of wavelets and decision trees to detect ships and other maritime surveillance targets from medium resolution SAR images. Wavelets have inherent advantages to extract image descriptors while decision trees are able to handle different data sources. In addition, our work aims to consider oceanic features such as ship wakes and ocean spills. In this incipient work, Haar and Cohen-Daubechies-Feauveau 9/7 wavelets obtain detailed descriptors from targets and ocean features and are inserted with other statistical parameters and wavelets into an oblique decision tree. © 2011 Springer-Verlag.