Preferred Language
Articles
/
joe-1666
An Empirical Investigation on Snort NIDS versus Supervised Machine Learning Classifiers
...Show More Authors

With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade the detection rates of current NIDSs, thorough analyses are essential to identify where ML predictors outperform them. The first step is to provide assessment of most used NIDS worldwide, Snort, and comparing its performance with ML classifiers. This paper provides an empirical study to evaluate performance of Snort and four supervised ML classifiers, KNN, Decision Tree, Bayesian net and Naïve Bays against network attacks, probing, Brute force and DoS. By measuring Snort metric, True Alarm Rate, F-measure, Precision and Accuracy and compares them with the same metrics conducted from applying ML algorithms using Weka tool. ML classifiers show an elevated performance with over 99% correctly classified instances for most algorithms, While Snort intrusion detection system shows a degraded classification of about 25% correctly classified instances, hence identifying Snort weaknesses towards certain attack types and giving leads on how to overcome those weaknesses. 

es.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Thu Jul 02 2020
Journal Name
Jasep المجلة العربية للعلوم التربوية والنفسية
Critical Thinking-Based Learning: Developments, Trends, and Values
...Show More Authors

In recent years, English language teaching and second language acquisition has demonstrated a significant accentuation upon basic reasoning abilities improvement in the language capability advancement. Encouraging a point of view of duty to training basic intuition aptitudes in accordance with the English language courses, this paper gives an account of an investigation directed at theoretical meanings of basic deduction, drifts about the centrality of basic speculation for language educating and associations between critical thinking and language learning. The educators have the focal pretended by basic intuition in successful language teaching method, identified to Ennis’ (2011) critical thinking categories. The skill of thinking critic

... Show More
View Publication Preview PDF
Publication Date
Sun Jan 31 2016
Journal Name
International Journal Of Research In Humanities, Arts, And Literature
THE PROBLEMS FACING IRAQI CHILDREN IN LEARNING ENGLISH
...Show More Authors

DBN Rashid, IMPAT: International Journal of Research in Humanities, Arts, and Literature, 2016 - Cited by 5

View Publication
Publication Date
Fri Jul 26 2024
Journal Name
Academia Open
Enhancing Pediatric Nursing Skills by Top Learning Strategies
...Show More Authors

Background: The efficacy of educational strategies is crucial for nursing students to competently perform pediatric procedures like nasogastric tube insertion. Specific Background: This study evaluates the effectiveness of simulation, blended, and self-directed learning strategies in enhancing these skills among nursing students. Knowledge Gap: Previous research lacks a comprehensive comparison of these strategies' impacts on skill development in pediatric nursing contexts. Aims: The study aims to assess the effectiveness of different educational strategies on nursing students' ability to perform pediatric nasogastric tube insertions. Methods: A pre-experimental design was employed at the College of Nursing, University of Baghdad, i

... Show More
View Publication
Crossref
Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
...Show More Authors

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

... Show More
View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes On Data Engineering And Communications Technologies
Utilizing Deep Learning Technique for Arabic Image Captioning
...Show More Authors

View Publication
Crossref (2)
Scopus Crossref
Publication Date
Fri Mar 18 2022
Journal Name
Aro-the Scientific Journal Of Koya University
Detecting Deepfakes with Deep Learning and Gabor Filters
...Show More Authors

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

... Show More
View Publication
Scopus (12)
Crossref (4)
Scopus Clarivate Crossref
Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Iraqi Sentiment and Emotion Analysis Using Deep Learning
...Show More Authors

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

... Show More
View Publication Preview PDF
Crossref (6)
Crossref
Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Applied Sciences And Nanotechnology
Microstructure Investigation of Activated Carbon Prepared from Potato Peel
...Show More Authors

Abstract This research investigates how activated carbon (AC) was synthesized from potato peel waste (PPW). Different ACs were synthesized under the atmosphere's conditions during carbonation via two activation methods: first, chemical activation, and second, carbon dioxide-physical activation. The influence of the drying period on the preparation of the precursor and the methods of activation were investigated. The specific surface area and pore volume of the activated carbon were estimated using the Brunauer–Emmett–Teller method. The AC produced using physical activation had a surface area as high as 1210 m2/g with a pore volume of 0.37 cm3/g, whereas the chemical activation had a surface area of 1210 m2/g with a pore volume of 0.34 c

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Mar 27 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Phytochemical Investigation and Antioxidant Activity of Iraqi Tribulus terrestris
...Show More Authors

The aim of the present study was to characterize the Iraqi Tribulus terrestris for the presence of biologically active phyto-chemicals using methanolic extracts of the plant (aerial parts) by Gas Chromatography –Mass spectrometry (GC/MS), while the mass spectra of the compounds found in the extract was matched with the National Institute of Standards and Technology (NIST) library , in addition to study the antioxidant activity of plant extract , results confirmed the presence of therapeutically potent compounds in the Iraqi Tribulus terrestris extract predominantly alkaloids, flavonoids, saponins, tannins and terpenoids. Antioxidant potential of Iraqi Tribulus terrestris

... Show More
View Publication Preview PDF
Crossref (4)
Crossref
Publication Date
Sat Jul 01 2017
Journal Name
International Journal Of Modern Physics E
Nuclear structure investigation of some neutron-rich halo nuclei
...Show More Authors

The ground state proton, neutron and matter densities, the corresponding rms radii and charge form factors of a dripline nuclei 6He, 11Li, 12Be and 14Be have been studied via a three–body model of (Core + n + n). The core–neutron interaction takes the form of Woods-Saxon (WS) potential. The two valence neutrons of 6He, 11Li and 12Be interact by the realistic interaction of ZBMII while those of 14Be interact via the realistic interaction of VPNP. The core and valence (halo) density distributions are described by the single-particle wave functions of the WS potential. The calculated results are discussed and compared with the experimental data. The long tail performance is clearly noticed in the calculated neutron and matter density distr

... Show More
View Publication
Scopus (14)
Crossref (9)
Scopus Clarivate Crossref