To protect the network, resources, and sensitive data, the intrusion detection system (IDS) has become a fundamental component of organizations that prevents cybercriminal activities. Several approaches have been introduced and implemented to thwart malicious activities so far. Due to the effectiveness of machine learning (ML) methods, the proposed approach applied several ML models for the intrusion detection system. In order to evaluate the performance of models, UNSW-NB 15 and Network TON_IoT datasets were used for offline analysis. Both datasets are comparatively newer than the NSL-KDD dataset to represent modern-day attacks. However, the performance analysis was carried out by training and testing the Decision Tree (DT), Gradient Boosting Tree (GBT), Multilayer Perceptron (MLP), AdaBoost, Long-Short Term Memory (LSTM), and Gated Recurrent Unit (GRU) for the binary classification task. As the performance of IDS deteriorates with a high dimensional feature vector, an optimum set of features was selected through a Gini Impurity-based Weighted Random Forest (GIWRF) model as the embedded feature selection technique. This technique employed Gini impurity as the splitting criterion of trees and adjusted the weights for two different classes of the imbalanced data to make the learning algorithm understand the class distribution. Based upon the importance score, 20 features were selected from UNSW-NB 15 and 10 features from the Network TON_IoT dataset. The experimental result revealed that DT performed well with the feature selection technique than other trained models of this experiment. Moreover, the proposed GIWRF-DT outperformed other existing methods surveyed in the literature in terms of the F1 score.

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Rate of spread of SARS-CoV-2 and number of relevant deaths continue to elevate as the time elapses since its first outbreak. With no readily available curative treatment neither any effective vaccine till now to prevent the infection, practicing personal protection measures remain the only effective way to stay protected from its attack. Those who are directly exposed to the care of any confirmed or suspected COVID-19 patient, including the health care workers and caregivers, have been advised by the World Health Organization (WHO) and Centre for Disease Control and Prevention (CDC) to wear proper face masks or respirators following the guidelines. Transmission of corona virus occurs through respiratory droplets, close personal contact as well as touching stuff or surfaces polluted by the viral particles. However, several studies have already proven the effectiveness of using various face masks, according to the circumstances, in preventing the dissemination of COVID-19. Bangladesh Journal of Infectious Diseases 2020;7(1):27-32

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