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An Empirical Investigation on Snort NIDS versus Supervised Machine Learning Classifiers
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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. 

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Publication Date
Wed Nov 27 2019
Journal Name
Iraqi Journal Of Science
Comparative Study of Some Virulence Factors and Analysis of Phylogenetic Tree by 16S rDNA Sequencing of Aeromonas hydrophila Isolated from Clinical and Environmental Samples
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     Aeromonas hydrophila is widely distributed throughout the world and causes diseases to animals and human exposed to contaminated environments such as water and soil. This study aimed to compare between isolates of A. hydrophila collected from clinical and environmental samples, through investigating the phenotype of some virulence factors in vitro, including hemolysin, protease, lipase, nuclease and biofilm formation ability. Also, the antimicrobial susceptibility for different antibiotics was determined using disc diffusion method. For genotypic identification of isolates and phylogenetic tree construction, 16S rDNA target gene was amplified and sequenced. The phenoty

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Publication Date
Tue Jun 01 2021
Journal Name
Periodicals Of Engineering And Natural Sciences
Steganography using dual tree complex wavelet transform with LSB indicator technique
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Image steganography is undoubtedly significant in the field of secure multimedia communication. The undetectability and high payload capacity are two of the important characteristics of any form of steganography. In this paper, the level of image security is improved by combining the steganography and cryptography techniques in order to produce the secured image. The proposed method depends on using LSBs as an indicator for hiding encrypted bits in dual tree complex wavelet coefficient DT-CWT. The cover image is divided into non overlapping blocks of size (3*3). After that, a Key is produced by extracting the center pixel (pc) from each block to encrypt each character in the secret text. The cover image is converted using DT-CWT, then the p

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Publication Date
Wed Feb 08 2023
Journal Name
Journal Of Educational And Psychological Researches
Activating the Role of Women Leaders in Educational Decision-Making in Educational Administrations in the Northern Border in Light of the Kingdom's 2030 Vision
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This study aims at identifying the activation of the role of feminine leaders in educational decision-making in educational administrations in the Northern Borders Province in light of the Kingdom's vision 2030. It also aims to identify what educational leadership is, to study the conceptual framework of the contemporary education decision-making process, and to examine the reality of the problems of feminine leaders in educational decision-making in the educational administrations in the Northern Borders. In addition, it tries to develop a proposed vision to activate the role of feminine leaders in educational decision-making in Educational Administrations in the Northern Borders Province in light of Vision 2030. To achieve the objectiv

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Molecular detection by some virulence genes of Salmonella enterica subsp. enterica isolated from the stool of children with diarrhea
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Diarrhea is a real disease in childhood which could cause death. Therefore, this study was conducted to isolate Salmonella from 350 stool samples taken from children under five years in age, suffering from diarrhea during the period from March 2019 to March 2020 in Tikrit city / Iraq. The results showed the possibility to isolate ten isolates of Salmonella enterica subsp. Enterica, an infection rate, represents 2.875% of the total rate of patients who suffer from diarrhea. The virulence genes were investigated for ten isolates of S. enterica subsp. enterica, the result is that all isolates possessed the genes stn, invA, lpfA with an appearance percentage of 100%, whi

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Publication Date
Mon Apr 17 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Simulation Expirment for Proofing the Theoretical Assumption of Time Complexity for Binary Search Tree
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      It is frequently asserted that an advantage of a binary search tree implementation of a set over linked list implementation is that for reasonably well balanced binary search trees the average search time (to discover whether or not a particular element is present in the set) is O(log N) to the base 2 where N is the number of element in the set (the size of the tree).  This paper presents an experiment for measuring and comparing the obtained binary search tree time with the expected time (theoretical), this experiment proved the correctness of the hypothesis, the experiment is carried out using a program in turbo Pascal with recursion technique implementation and a statistical method  to prove th

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Data Mining Techniques for Iraqi Biochemical Dataset Analysis
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This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

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Publication Date
Tue Mar 01 2022
Journal Name
The International Journal Of Nonlinear Analysis And Applications
Improved optimality checkpoint for decision making by using the sub-triangular form
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Decision-making in Operations Research is the main point in various studies in our real-life applications. However, these different studies focus on this topic. One drawback some of their studies are restricted and have not addressed the nature of values in terms of imprecise data (ID). This paper thus deals with two contributions. First, decreasing the total costs by classifying subsets of costs. Second, improving the optimality solution by the Hungarian assignment approach. This newly proposed method is called fuzzy sub-Triangular form (FS-TF) under ID. The results obtained are exquisite as compared with previous methods including, robust ranking technique, arithmetic operations, magnitude ranking method and centroid ranking method. This

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The effect of marketing vigilance in attracting deposits: Applied research in a sample of private commercial bank
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The aim of the research is to demonstrate the impact of the dimensions of the marketing vigilance represented by (environmental scanning, diagnostic capacity, validity and decision-making) and to attract deposits represented by (customer relationship management strategy, distribution strategy (location), promotion strategy), as the research was applied in each of Banks (Assyria International, Iraqi Middle East Investment, Business Bay, Iraqi Investment, Babel, Al Mansour Investment), and the questionnaire was adopted as a main tool for collecting data and information from a sample of (110) who are in the position (department manager, department manager, assistant Section Director, Division Officer, Unit Officer), and the statistical prog

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Publication Date
Mon Jan 27 2020
Journal Name
Iraqi Journal Of Science
Software Development for First Aid Decision Support System
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This work presents an approach to deal with modelling a decision support system framework to introduce an application for decisions in medical knowledge system analysis. First aid is extremely important worldwide and, hence, a decision support framework, know as First Aid Decision Support System (FADSS), was designed and implemented to access experimental cases exerting danger to the general population, offering advanced conditions for testing abilities in research and arranging an emergency treatment through the graphical user interface (UI). The design of first aid treatment in FADSS depends on the general cases in first aid. We presented a strategy to manage first aid treatment  by modelling an application (FADSS) that assists pe

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Publication Date
Sat Mar 28 2020
Journal Name
Iraqi Journal Of Science
Effect of levels in Dual Tree Complex Wavelet Transform when design Universal image stego-analytic
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Universal image stego-analytic has become an important issue due to the natural images features curse of dimensionality. Deep neural networks, especially deep convolution networks, have been widely used for the problem of universal image stegoanalytic design. This paper describes the effect of selecting suitable value for number of levels during image pre-processing with Dual Tree Complex Wavelet Transform. This value may significantly affect the detection accuracy which is obtained to evaluate the performance of the proposed system. The proposed system is evaluated using three content-adaptive methods, named Highly Undetetable steGO (HUGO), Wavelet Obtained Weights (WOW) and UNIversal WAvelet Relative Distortion (UNIWARD).
The obtain

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