ATTACK DETECTION IN ENTERPRISE NETWORKS BY MACHINE LEARNING METHODS

Detection of network attacks is currently one of the most important problems of secure use of enterprise networks. Network signature-based intrusion detection systems cannot detect new types of attacks. Thus, the urgent task is to quickly classify network traffic to detect network attacks. The article describes algorithms for detecting attacks in enterprise networks based on data analysis that can be collected in them. The UNSW-NB15 data set was used to compare machine learning methods for classifying attack or-normal traffic, as well as to identify nine more popular classes of typical attacks, such as Fuzzers, Analysis, Backdoors, DoS, Exploits, Generic, Reconnaissance, Shellcode and Worms. Balanced accuracy is used as the main metric for assessing the accuracy of the classification. The main advantage of this metric is an adequate assessment of the accuracy of classification algorithms given the strong imbalance in the number of marked records for each class of data set. As a result of the experiment, it was found that the best algorithm for identifying the presence of an attack is RandomForest, to clarify its type - AdaBoost

Optical spectroscopy of nanoporous membranes based on anodic alumina in an ammonia gas flow

Background and Objectives: Membranes in the form of highly ordered nanostructures of porous anodic aluminum oxide (PAAO) with adjustable pore properties were obtained by electrochemical anodizing. PAAO nanostructures were prepared in an oxalic acid electrolyte at a direct current electrochemical potential of 30–60 V. The ready-made nanoporous membranes were modified with thin silver films 1.8, 3.6 and 5.4 nm thick. The study of the membrane surface by scanning electron microscopy has shown that nanoporous membranes have hexagonally arranged and highly ordered arrays of pores with a diameter of (30±4) nm and a packing density of about 1.8 · 10¹⁰ cm–2. Optical interference spectra of PAAO were recorded in the wavelength range of 300–900 nm. The optical properties of nanoporous membranes with a free and silver-modified surface changed depending on the time of interaction of the membrane surface with the ammonia gas flow, which led to changes in the interference pattern and, in turn, to changes in the effective optical thickness (EOT) of the membranes. Features of the influence of the membrane surfacemodified with silver onthe shape and sensitivity ofthe optical signal ofthe sensor have been revealed. The aim ofthis work was to experimentally study the temporal characteristics of the optical spectral response of nanoporous anodic alumina membranes with a free pore surface and modified with thin silver films in an ammonia gas flow. Materials and Methods: The thickness of the PAAO membrane, determined profilometrically, did not exceed 1.0 µm. The average inner diameter of Al2O3 nanopores is (30±4) nm. The silver films were deposited by magnetron sputtering at direct current. Changes in the effective optical thickness are used to quantify changes in the optical properties of the membrane. Changes in the effective optical thickness will be mainly determined by the effective refractive index of the PAAO-Ag molecular film of the adsorbed gas structure. The effective refractive index of the membrane was determined from the measured position of the interference maxima and the given membrane thickness. Results: Association processes have been considered, i.e. binding of analyte molecules to the surface of the PAAO nanoporous membrane. A stream of gaseous ammonia was chosen as the analyte. According to the Langmuir isotherm model, the sensor response during real-time measurements should follow a negative exponential trend. It has been shown that the shape of the sensor’s optical signal qualitatively repeats the shape of the theoretical curve of real-time optical probing in the regions of molecular binding and equilibrium. The molecular association time of the free surface of the PAAO nanoporous membrane was 7 ± 1 minutes. The deposition of thin silver films on the surface of a nanoporous PAAO membrane leads to a change in the shape of the optical signal and a decrease in its magnitude. Conclusion: On the basis of the synthesized nanoporous PAAO membranes with a free surface and modified with ultrathin silver films, experimental studies of the effect of ammonia flow on multibeam light interference in such membranes have been carried out. It has been found that the surface roughness and size effect of the silver film thickness have a significant effect on the transmission spectra and sensory sensitivity of the membranes. It has been shown that the largest relative change in the refractive index of the membrane in an ammonia flow is observed for the thinnest silver film 1.8 nm thick. It has been noted that there is a threshold value of the thickness of a silver film deposited on the surface of a nanoporous PAAО membrane, above which the use of such films in optical sensors with the mechanism of multipath light interference is not advisable, and the use of a different mechanism is required, for example, the mechanism of localized surface plasmon resonance

fMRI study of brain activity in men and women during rhythm reproduction and measuring short time intervals

The aim of the research was to study the men and women brain activity in during memorizing and reproducing rhythm (5 s) and measuring short time intervals (0.8 s) by fMRI method. Volunteers are young people (boys and girls) aged 18 to 27 years. It was shown that extensive brain areas (prefrontal and motor cortex, insular cortex, sensory and associative areas of the parietal and temporal cortex, amygdala, hippocampus, thalamus, basal ganglia and cerebellum) are involved in providing sensorimotor activity associated with rhythm reproduction and measuring short time intervals. It was found that the measurement of short time intervals is partially provided by the same brain structures as the rhythm reproduction. When measuring the duration, the activation in both hemisphere of a number of additional structures (frontal pole, supraorbital gyrus, angular gyrus, temporal area and some other cortical areas) was detected. The results of this study indicate that the brain support of sensorimotor activity associated with rhythm reproduction and measuring short time intervals significantly depends on the method of scaling time intervals and gender differences

Mirror neurons in the interpretation of action and intentions

The aim of the research was the studying the activity of mirror neurons in humans during the observation and reproduction of rhythm. As markers of mirror neuron activity, we used depression of the EEG mu-rhythm in the alpha and beta frequency ranges, cortical interactions at the frequency of this rhythm, as well as the results of fMRI brain mapping. The research involved volunteers men and women aged from 18 to 27 year (University students). Research has shown that monitoring the reproduction of a five-second rhythm is accompanied by activation of not only those areas of the cortex where the «motor» mirror neurons are located, but also other cortex areas, as well as the basal ganglia and cerebellum. This findings suggest that mirror neurons themselves do not provide an understanding of actions and intentions, although they are involved in these processes. It is assumed that these neurons provide interaction between the prefrontal, sensory and motor areas of the cortex, as well as places where motor programs are stored in the brain. The result of the interaction of these structures is an understanding of the actions and intentions of other people

Synthesis, Structure, and Characterization of Chromo(fluoro)ionophores with Cation-Triggered Emission Based on <i>N</i>‑Methylaza-Crown-Ether Styryl Dyes

Novel 2-benzothiazole-, 4-pyridine-, and 2- and 4-quinoline-based styryl dyes containing an <i>N</i>-methylbenzoaza-15­(18)-crown-5­(6)-ether moiety were synthesized. A detailed electronic spectroscopy study revealed high performance of these compounds as optical molecular sensors for alkali and alkaline-earth metal cations. They were shown to considerably surpass analogous chromoionophores based on <i>N</i>-phenylaza-crown ethers regarding both the ionochromism and the cation-binding ability. In addition, they act as fluorescent sensors for the metal cations by demonstrating cation-triggered emission. Upon complexation with Ba²⁺, the fluorescence enhancement factor reaches 61. The structural features of dyes and their metal complexes were studied by NMR spectroscopy and X-ray diffraction. The high degree of macrocycle preorganization was found to be one of the factors determining the high cation-binding ability of the sensor molecules based on <i>N</i>-methylbenzoaza-crown ethers

Identification of Genetic Risk Factors of Severe COVID-19 Using Extensive Phenotypic Data: A Proof-of-Concept Study in a Cohort of Russian Patients

The COVID-19 pandemic has drawn the attention of many researchers to the interaction between pathogen and host genomes. Over the last two years, numerous studies have been conducted to identify the genetic risk factors that predict COVID-19 severity and outcome. However, such an analysis might be complicated in cohorts of limited size and/or in case of limited breadth of genome coverage. In this work, we tried to circumvent these challenges by searching for candidate genes and genetic variants associated with a variety of quantitative and binary traits in a cohort of 840 COVID-19 patients from Russia. While we found no gene- or pathway-level associations with the disease severity and outcome, we discovered eleven independent candidate loci associated with quantitative traits in COVID-19 patients. Out of these, the most significant associations correspond to rs1651553 in MYH14p = 1.4 &times; 10&minus;7), rs11243705 in SETX (p = 8.2 &times; 10&minus;6), and rs16885 in ATXN1 (p = 1.3 &times; 10&minus;5). One of the identified variants, rs33985936 in SCN11A, was successfully replicated in an independent study, and three of the variants were found to be associated with blood-related quantitative traits according to the UK Biobank data (rs33985936 in SCN11A, rs16885 in ATXN1, and rs4747194 in CDH23). Moreover, we show that a risk score based on these variants can predict the severity and outcome of hospitalization in our cohort of patients. Given these findings, we believe that our work may serve as proof-of-concept study demonstrating the utility of quantitative traits and extensive phenotyping for identification of genetic risk factors of severe COVID-19

Alirocumab and cardiovascular outcomes after acute coronary syndrome

BACKGROUN

Alirocumab and Cardiovascular Outcomes after Acute Coronary Syndrome

BACKGROUN