Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an SVM-based DDoS detection model shows superior performance. This comparative analysis offers a valuable insight into the development of efficient and accurate techniques for detecting DDoS attacks in SDN environments with less complexity and time.
Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.
In this paper we have been focus for the comparison between three forms for classification data belongs
... Show MoreThe purpose of this article is to improve and minimize noise from the signal by studying wavelet transforms and showing how to use the most effective ones for processing and analysis. As both the Discrete Wavelet Transformation method was used, we will outline some transformation techniques along with the methodology for applying them to remove noise from the signal. Proceeds based on the threshold value and the threshold functions Lifting Transformation, Wavelet Transformation, and Packet Discrete Wavelet Transformation. Using AMSE, A comparison was made between them , and the best was selected. When the aforementioned techniques were applied to actual data that was represented by each of the prices, it became evident that the lift
... Show MoreRecently, dental implants have experienced increasing demand as one of the most effective, permanent and stable ways for replacing missing teeth. However, peri-implant diseases that are multispecies plaque-based infections may ultimately lead to implant failure (i.e., late peri-implantitis). Therefore, the present study aims to detect the microbial diversity of subgingival plaque in peri-implantitis cases (N = 30) by comparing with healthy implants (N = 34) using culture-based identification methods, including VITEK 2 system. An increase in microbial diversity (29 species along with 1 and 7 isolates, which were classified as a genus and unidentified species, respectively) were observed in subgingival sites of diseased implants dominated by
... Show MoreKE Sharquie, AA Noaimi, MM Al-Salih, Saudi Medical Journal, 2008 - Cited by 56
The environmental surfaces hygiene of college premises like classrooms play role in spreading different pathogenic bacteria, furthermore a Medical students are often potential vectors for resistant bacteria to their entourage. This study aimed to assess bacterial contamination and their susceptibility to various antimicrobial agents in the educational classroom of Al-Kindy College of medicine in two classrooms: one occupied by clinical visitor and non-clinical visitor students to evaluate and determine its health risk. In this cross-sectional study, different sites of the educational classroom of Al-Kindy College of medicine were studied. Ninety-sex Different swab samples were collected from 8 different sites of college across bot
... Show MoreIn this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.
The study aimed to evaluate the level of MMP‑2 in acute myeloid leukemia (AML) patients in comparison with that in remission status, and healthy subjects, and to find its correlation with hematologic parameters. This study included sixty newly diagnosed AML patients. Remission status was assessed after induction chemotherapy. The overall survival (OS) was determined after 6 months. The plasma MMP‑2 level was measured at diagnosis by enzyme immunoassay. Twenty‑eight healthy individuals were recruited as a control group. Plasma MMP‑2 was higher in AML patients than in healthy individuals (P = 0.005). The level of MMP‑2 was much higher in the M5 subtype than in the other subtypes (P = 0.0001). There was no statistically significant d
... Show MoreS Khalifa E, N Adil A, AS Mazin M…, 2008