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.
In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation) structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of these procedures and compare them using generated data.
Background: Chronic otitis media (COM) of mucosal or squamous type is a common problem in otolaryngology practice, the active form of COM is characterized by discharge of pus and is treated by antibiotics to start with, the appropriate antibiotic should be prescribed to avoid antibiotic abuse and guarantee good outcome. Objectives:The objective of this study is to identify the causative organisms of active chronic active otitis media both (mucosal, squamous) type and test their sensitivity to various anti- microbial agents &compare with abroad studies.Methods:A prospective study was done on eighty patients, different ages and sexes were taken and carful history and examination was done, examination under microscope was done with carf
... Show MoreRouting protocols are responsible for providing reliable communication between the source and destination nodes. The performance of these protocols in the ad hoc network family is influenced by several factors such as mobility model, traffic load, transmission range, and the number of mobile nodes which represents a great issue. Several simulation studies have explored routing protocol with performance parameters, but few relate to various protocols concerning routing and Quality of Service (QoS) metrics. This paper presents a simulation-based comparison of proactive, reactive, and multipath routing protocols in mobile ad hoc networks (MANETs). Specifically, the performance of AODV, DSDV, and AOMDV protocols are evaluated and analyz
... Show MoreThe use of non-parametric models and subsequent estimation methods requires that many of the initial conditions that must be met to represent those models of society under study are appropriate, prompting researchers to look for more flexible models, which are represented by non-parametric models
In this study, the most important and most widespread estimations of the estimation of the nonlinear regression function were investigated using Nadaraya-Watson and Regression Local Ploynomial, which are one of the types of non-linear
... Show MorePolyethersulfone (PES) ultrafiltration membrane blending NaX zeolite crystals as a hydrophilic additive was examined for zinc (II) and lead ions Pb (II) removal from aqueous solutions. The effect of NaX zeolite content on the permeation flux and removal efficiency was studied. The results showed that adding zeolite to the polymer matrix enhanced the permeation flux. The permeation flux of all the zeolite/PES matrix membranes was higher than the pristine membrane. No significant improvement was observed in the removal of Zn (II) ions using all prepared membranes as the removal percentage did not raise above 29.2%. However, the removal percentage of Pb (II) ions was enhanced to 97% using a membrane containing 0.9%wt. zeolite. Also, it was
... Show MoreThe question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.
In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes
... Show MoreThe porosity of materials is important in many applications, products and processes, such as electrochemical devices (electrodes, separator, active components in batteries), porous thin film, ceramics, soils, construction materials, ..etc. This can be characterized in many different methods, and the most important methods for industrial purposes are the N2 gas adsorption and mercury porosimetry. In the present paper, both of these techniques have been used to characterize some of Iraqi natural raw materials deposits. These are Glass Sand, Standard Sand, Flint Clay and Bentonite. Data from both analyses on the different types of natural raw materials deposits are critically examined and discussed. The results of specific surface are
... Show MoreThe detection of diseases affecting plant is very important as it relates to the issue of food security, which is a very serious threat to human life. The system of diagnosis of diseases involves a series of steps starting with the acquisition of images through the pre-processing, segmentation and then features extraction that is our subject finally the process of classification. Features extraction is a very important process in any diagnostic system where we can compare this stage to the spine in this type of system. It is known that the reason behind this great importance of this stage is that the process of extracting features greatly affects the work and accuracy of classification. Proper selection of
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