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An Internet of Things Botnet Detection Model Using Regression Analysis and Linear Discrimination Analysis

The Internet of Things (IoT) has become a hot area of research in recent years due to the significant advancements in the semiconductor industry, wireless communication technologies, and the realization of its ability in numerous applications such as smart homes, health care, control systems, and military. Furthermore, IoT devices inefficient security has led to an increase cybersecurity risks such as IoT botnets, which have become a serious threat. To counter this threat there is a need to develop a model for detecting IoT botnets.

This paper's contribution is to formulate the IoT botnet detection problem and introduce multiple linear regression (MLR) for modelling IoT botnet features with discriminating capability and alleviating the challenges of IoT detection. In addition, a linear discrimination analysis (LDA) model for distinguishing between normal activities and IoT botnets was developed.

Network-based detection of IoT (N-BaIoT) dataset was used to evaluate the performance of the proposed IoT botnet detection model in terms of accuracy, precision, and detection rate.  Experimental results revealed that the proposed IoT botnet detection model provides a relevant feature subset and preserves high accuracy when compared with state-of-the-art and baseline methods, particularly LDA.

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of Models (NAGARCH & APGARCH) by Using Simulations

Simulation experiments are a means of solving in many fields, and it is the process of designing a model of the real system in order to follow it and identify its behavior through certain models and formulas written according to a repeating software style with a number of iterations. The aim of this study is to build a model  that deals with the behavior suffering from the state of (heteroskedasticity) by studying the models (APGARCH & NAGARCH) using (Gaussian) and (Non-Gaussian) distributions for different sample sizes (500,1000,1500,2000) through the stage of time series analysis (identification , estimation, diagnostic checking and prediction). The data was generated using the estimations of the parameters resulting f

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Publication Date
Sun Aug 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
STATISTICAL ANALYSIS OF PATIENTS INFECTED WITHCORONAVIRUS USING MANOVA

Statistics has an important role in studying the characteristics of diverse societies. By using statistical methods, the researcher can make appropriate decisions to reject or accept statistical hypotheses. In this paper, the statistical analysis of the data of variables related to patients infected with the Coronavirus was conducted through the method of multivariate analysis of variance (MANOVA) and the statement of the effect of these variables.

Publication Date
Fri Jan 01 2016
Journal Name
Ieee Access
Towards an Applicability of Current Network Forensics for Cloud Networks: A SWOT Analysis

In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Using the Logistic Regression Model in Studding the Assistant Factors to Diagnose Bladder Cancer

The cancer is one of the biggest health problems that facing the world . And  the bladder cancer has a special place among the most spread cancers in Arab countries specially in Iraq and Egypt(2) . It is one of the diseases which can be treated and cured if it is diagnosed early . This research is aimed at studying the assistant factors that diagnose bladder cancer such as (patient's age , gender , and other major complains of hematuria , burning or pain during urination and micturition disorders) and then determine which factors are the most effective in the possibility of diagnosing this disease by using the statistical model (logistic regression model) and depending on a random sample of (128) patients . After

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Publication Date
Mon Jan 27 2020
Journal Name
Iraqi Journal Of Science
Sentiment Analysis in Social Media using Machine Learning Techniques

Over the last period, social media achieved a widespread use worldwide where the statistics indicate that more than three billion people are on social media, leading to large quantities of data online. To analyze these large quantities of data, a special classification method known as sentiment analysis, is used. This paper presents a new sentiment analysis system based on machine learning techniques, which aims to create a process to extract the polarity from social media texts. By using machine learning techniques, sentiment analysis achieved a great success around the world. This paper investigates this topic and proposes a sentiment analysis system built on Bayesian Rough Decision Tree (BRDT) algorithm. The experimental results show

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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of The College Of Languages (jcl)
A traditional model of translation: Critical analysis: Традиционные модели перевода: критический анализ

 

 The article critically analyzes traditional translation models. The most influential models of translation in the second half of the 20th century have been mentioned, among which the theory of formal and dynamic equivalence, the theory of regular correspondences, informative, situational-denotative, functional-pragmatic theory of communication levels have been considered. The selected models have been analyzed from the point of view of the universality of their use for different types and types of translation, as well as the ability to comprehend the deep links established between the original and the translation.

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Physics: Conference Series
Bayesian Computational Methods of the Logistic Regression Model
Abstract<p>In this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.</p>
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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Development an Anomaly Network Intrusion Detection System Using Neural Network

Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

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Publication Date
Sat Jan 01 2022
Journal Name
Ssrn Electronic Journal
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Publication Date
Sun Oct 02 2011
Journal Name
The Iraqi Journal Of Agricultural Sciences
AN ECONOMIC ANALYSIS OF PRODUCTION AND CONSUMPTION OF SUGAR CANE AND SUGAR BEET IN IRAQ

In spite of economic importance of sugar cane and sugar beet as they described as industrial crops they still face decreasing rates of production and productivity in Iraq , and their production was not able to satisfy the local industrial demands for sugar . Thus this study aimed at studying and analyzing, production and productivity of sugar cane and sugar beet in Iraq and this has been done by using non serial data that can be obtained from official offices in Iraq . The area and production of sugar cane in Iraq recorded positive annual growth rates during 1970- 1978 which were 6% and 5% consequently , while the productivity of sugar cane recorded at the same duration of time negative annual growth rate which was 1% , while they recorded

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