Data Mining for Network Intrusion Detection : A comparison of data mining algorithms and an analysis of relevant features for detecting cyber-attacks

Data mining can be defined as the extraction of implicit, previously un-known, and potentially useful information from data. Numerous re-searchers have been developing security technology and exploring new methods to detect cyber-attacks with the DARPA 1998 dataset for Intrusion Detection and the modified versions of this dataset KDDCup99 and NSL-KDD, but until now no one have examined the performance of the Top 10 data mining algorithms selected by experts in data mining. The compared classification learning algorithms in this thesis are: C4.5, CART, k-NN and Naïve Bayes. The performance of these algorithms are compared with accuracy, error rate and average cost on modified versions of NSL-KDD train and test dataset where the instances are classified into normal and four cyber-attack categories: DoS, Probing, R2L and U2R. Additionally the most important features to detect cyber-attacks in all categories and in each category are evaluated with Weka’s Attribute Evaluator and ranked according to Information Gain. The results show that the classification algorithm with best performance on the dataset is the k-NN algorithm. The most important features to detect cyber-attacks are basic features such as the number of seconds of a network connection, the protocol used for the connection, the network service used, normal or error status of the connection and the number of data bytes sent. The most important features to detect DoS, Probing and R2L attacks are basic features and the least important features are content features. Unlike U2R attacks, where the content features are the most important features to detect attacks.

Automatic Glaucoma Detection Based on Optic Disc Segmentation and Texture Feature Extraction

The use of digital image processing techniques is prominent in medical settings for the automatic diagnosis of diseases. Glaucoma is the second leading cause of blindness in the world and it has no cure. Currently, there are treatments to prevent vision loss, but the disease must be detected in the early stages. Thus, the objective of this work is to develop an automatic detection method of Glaucoma in retinal images. The methodology used in the study were: acquisition of image database, Optic Disc segmentation, texture feature extraction in different color models and classification of images in glaucomatous or not. We obtained results of 93% accuracy

Determination Of Tetrakis(hydroxymethyl)phosphonium Sulfate In Commercial Formulations And Cooling Water By Capillary Electrophoresis With Contactless Conductivity Detection.

A novel capillary electrophoresis method using capacitively coupled contactless conductivity detection is proposed for the determination of the biocide tetrakis(hydroxymethyl)phosphonium sulfate. The feasibility of the electrophoretic separation of this biocide was attributed to the formation of an anionic complex between the biocide and borate ions in the background electrolyte. Evidence of this complex formation was provided by (11) B NMR spectroscopy. A linear relationship (R(2) = 0.9990) between the peak area of the complex and the biocide concentration (50-900 μmol/L) was found. The limit of detection and limit of quantification were 15.0 and 50.1 μmol/L, respectively. The proposed method was applied to the determination of tetrakis(hydroxymethyl)phosphonium sulfate in commercial formulations, and the results were in good agreement with those obtained by the standard iodometric titration method. The method was also evaluated for the analysis of tap water and cooling water samples treated with the biocide. The results of the recovery tests at three concentration levels (300, 400, and 600 μmol/L) varied from 75 to 99%, with a relative standard deviation no higher than 9%.

Development of instrumentation for amperometric and coulometric detection using ultramicroelectrodes

In this work it is presented the development of a simple, portable and inexpensive instrumentation for amperometric and coulometric detection in different analytical instrumentation systems utilizing ultramicroelectrodes. The software, developed in LabVIEW 7.1TM, is capable to carry out three main detection techniques (amperometric, pulsed amperometric and coulometric detection) and a voltammetric technique (cyclic voltammetry). The instrumentation was successfully evaluated using the following systems: cyclic voltammograms of metallic electrodes in alkaline solutions, flow electrochemical detection of glucose and glycine and direct determination of herbicide glyphosate (electrochemical detection coupled to HPLC).

Development and validation of a simple and rapid capillary zone electrophoresis method for determination of nnrti nevirapine in pharmaceutical formulations

A simple and fast capillary zone electrophoresis (CZE) method has been developed and validated for quantification of a non-nucleoside reverse transcriptase inhibitor (NNRTI) nevirapine, in pharmaceuticals. The analysis was optimized using 10 mmol L-1 sodium phosphate buffer pH 2.5, +25 kV applied voltage, hydrodynamic injection 0.5 psi for 5 s and direct UV detection at 200 µm. Diazepam (50.0 µg mL-1) was used as internal standard. Under these conditions, nevirapine was analyzed in approximately less than 2.5 min. The analytical curve presented a coefficient of correlation of 0.9994. Limits of detection and quantification were 1.4 µg mL-1 and 4.3 µg mL-1, respectively. Intra- and inter-day precision expressed as relative standard deviations were 1.4% and 1.3%, respectively and the mean recovery was 100.81%. The active pharmaceutical ingredient was subjected to hydrolysis (acid, basic and neutral) and oxidative stress conditions. No interference of degradation products and tablet excipients were observed. This method showed to be rapid, simple, precise, accurate and economical for determination of nevirapine in pharmaceuticals and it is suitable for routine quality control analysis since CE offers benefits in terms of quicker method development and significantly reduced operating costs.

Detection of dengue virus in saliva and urine by real time RT-PCR

Early diagnosis of dengue virus (DENV) infection is important for patient management and control of dengue outbreaks. The objective of this study was to analyze the usefulness of urine and saliva samples for early diagnosis of DENV infection by real time RT-PCR. Two febrile patients, who have been attended at the General Hospital of the School of Medicine of Ribeirao Preto, Sao Paulo University were included in the study. Serum, urine and saliva samples collected from both patients were subjected to real time RT-PCR for DENV detection and quantification. Dengue RNA was detected in serum, urine and saliva samples of both patients. Patient 1 was infected with DENV-2 and patient 2 with DENV-3. Data presented in this study suggest that urine and saliva could be used as alternative samples for early diagnosis of dengue virus infection when blood samples are difficult to obtain, e.g.,in newborns and patients with hemorrhagic syndromes.

Offline Detection, Identification, and Correction of Branch Parameter Errors Based on Several Measurement Snapshots

This paper proposes a three-stage offline approach to detect, identify, and correct series and shunt branch parameter errors. In Stage 1 the branches suspected of having parameter errors are identified through an Identification Index (II). The II of a branch is the ratio between the number of measurements adjacent to that branch, whose normalized residuals are higher than a specified threshold value, and the total number of measurements adjacent to that branch. Using several measurement snapshots, in Stage 2 the suspicious parameters are estimated, in a simultaneous multiple-state-and-parameter estimation, via an augmented state and parameter estimator which increases the V - theta state vector for the inclusion of suspicious parameters. Stage 3 enables the validation of the estimation obtained in Stage 2, and is performed via a conventional weighted least squares estimator. Several simulation results (with IEEE bus systems) have demonstrated the reliability of the proposed approach to deal with single and multiple parameter errors in adjacent and non-adjacent branches, as well as in parallel transmission lines with series compensation. Finally the proposed approach is confirmed on tests performed on the Hydro-Quebec TransEnergie network.

Repeated disturbances and canopy disturbance regime in a tropical semi-deciduous forest

The canopy disturbance regime and the influence of gap methods on the interpretation of forest structure and dynamics were evaluated in a tropical semi-deciduous forest in south-eastern Brazil. We encountered a gap density of 11.2 gaps ha(-1) and an average size which varied from 121 to 333 m(2) depending on the gap delimitation method considered (minimum gap size was 10 m(2)). Although average size was slightly higher, the median value obtained (78 m(2)) was comparable to other tropical forest sites and the gap size-class distribution found supported the pattern described for such forest sites. Among 297 gap makers, snapping and uprooting were the most common modes of disturbance. The number and basal area of gap makers were good predictors of gap size. Almost 25% of all gaps suffered from repeated disturbance events that brought about larger gap sizes. Such processes, along with delimitation methods, strongly influenced the estimation of turnover rate and therefore the interpretation of forest dynamics. These results demonstrated the importance of further studies on repeated disturbances, which is often neglected in forest studies.

Development and validation of a method for quantitative determination of econazole nitrate in cream formulation by capillary zone electrophoresis

A simple, fast, inexpensive and reliable capillary zone electrophoresis (CZE) method for the determination of econazole nitrate in cream formulations has been developed and validated. Optimum conditions comprised a pH 2.5 phosphate buffer at 20 mmol L(-1) concentration, +30 kV applied voltage in a 31.5 cm x 50 mu m I.D. capillary. Direct UV detection at 200 nm led to an adequate sensitivity without interference from sample excipients. A single extraction step of the cream sample in hydrochloric acid was performed prior to injection. Imidazole (100 mu g mL(-1)) was used as internal standard. Econazole nitrate migrates in approximately 1.2 min. The analytical curve presented a coefficient of correlation of 0.9995. Detection and quantitation limits were 1.85 and 5.62 mu g mL(-1), respectively. Excellent accuracy and precision were obtained. Recoveries varied from 98.1 to 102.5% and intra- and inter-day precisions, calculated as relative standard deviation (RSD), were better than 2.0%. The proposed CZE method presented advantageous performance characteristics and it can be considered suitable for the quality control of econazole nitrate cream formulations. (c) 2008 Elsevier B.V. All rights reserved.

Enantioselective analysis of propranolol and 4-hydroxypropranolol by CE with application to biotransformation studies employing endophytic fungi

A CE method is described for the enantioselective analysis of propranolol (Prop) and 4-hydroxypropranolol (4-OH-Prop) in liquid Czapek medium with application in the study of the enantioselective biotransformation of Prop by endophytic fungi. The electrophoretic conditions previously optimized were as follows: an uncoated fused-silica capillary, 4%w/v carboxymethyl-beta-CD in 25 mmol/L triethylamine/phosphoric acid (H(3)PO(4)) buffer at pH 9 as running electrolyte and 17 kV of voltage. UV detection was carried out at 208 nm. Liquid-liquid extraction using diethyl ether: ethyl acetate (1:1 v/v) as extractor solvent was employed for sample preparation. The calibration curves were linear over the concentration range of 0.25-10.0 mu g/mL for each 4-OH-Prop enantiomer and 0.10-10.0 mu g/mL for each Prop enantiomer (r >= 0.995). Within-day and between-day relative standard deviations and relative errors for precision and accuracy were lower than 15% for all the enantiomers. Finally, the validated method was used to evaluate Prop biotransformation in its mammalian metabolite 4-OH-Prop by some selected endophytic fungi. The screening of five strains of endophytic fungi was performed and all of them could biotransform Prop to some extent. Specifically, Glomerella cingulata (VA1) biotransformed 47.8% of (-)-(S)-Prop to (-)-(S)-4-OH-Prop with no formation of (+)-(R)4-OH-Prop in 72 h of incubation.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

A common inhibitory binding site for zinc and odorants at the voltage-gated K+ channel of rat olfactory receptor neurons

This study compared the effects of zinc and odorants on the voltage-gated K+ channel of rat olfactory neurons. Zinc reduced current magnitude, depolarized the voltage activation curve and slowed activation kinetics without affecting inactivation or deactivation kinetics. Zinc inhibition was potentiated by the NO compound, S-nitroso-cysteine. The pH- and diethylpyrocarbonate-dependence of zinc inhibition suggested that zinc acted by binding to histidine residues. Cysteine residues were eliminated as contributing to the zinc-binding site. The odorants, acetophenone and amyl acetate, also reduced current magnitude, depolarized the voltage activation curve and selectively slowed activation kinetics. Furthermore, the diethylpyrocarbonate- and pH-dependence of odorant inhibition implied that the odorants also bind to histidine residues. Zinc inhibitory potency was dramatically diminished in the presence of odorants, implying competition for a common binding site. These observations indicate that the odorants and zinc share a common inhibitory binding site on the external surface of the voltage-gated K+ channel.

An ultrasound based computer-aided diagnosis tool for steatosis detection

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.

Molecular diversity of bla genes in Klebsiella pneumoniae and Escherichia coli isolates

Dissertation presented to obtain a Ph.D. degree in Biology, speciality Microbiology, by Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Radiometric detection of metabolic activity of Paracoccidioides brasiliensis and its susceptibility to amphotericin B and diethylstilbestrol

Paracoccidioidomycosis (South American blastomycosis) is a systemic disease, strikingly more frequent in males, caused by the dimorphic fungus Paracoccidioides brasiliensis. A radiometric assay system has been applied to study the metabolic activity and the effect of drugs on this fungus "in vitro". The Y form of the yeast, grown in liquid Sabouraud medium was inoculated into sterile reaction vials containing the 6B aerobic medium along with 2.0 μCi of 14C-substrates. Control vials, prepared in the same way, contained autoclaved fungi. To study the effects of amphotericin B (AB) (0.1 and 10 μg/ml) and diethylstilbestrol (DSB) (1.0, 5.0 and 10 μg/ml) extra controls with live fungi and no drug were used. All vials were incubated at 35°C and metabolism measured daily with a Bactec instrument. 14CO2 production by P. brasiliensis was slow and could be followed for as long as 50 days. AB at 10mg/ml and DSB at 5 μg/ml inhibited the metabolism and had a cidal effect on this fungus. The results with DSB might explain the low incidence of the disease in females. This technique shows promise for studying metabolic pathways, investi gating more convenient 14C-substrates to expedite radiometric detection and for monitoring the effects of other drugs and factors on the metabolism of P. brasiliensis "in vitro".