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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
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Permeability Prediction and Facies Distribution for Yamama Reservoir in Faihaa Oil Field: Role of Machine Learning and Cluster Analysis Approach
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
An Investigation into Heat Transfer Enhancement by Using Oscillating Fins
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The present work describes numerical and experimental investigation of the heat transfer characteristics in a plate-fin, having built-in piezoelectric actuator mounted on the base plate (substrate). The geometrical configuration considered in the present work is representative of a single element of the plate-fin and triple fins. Air is taken as the working fluid. A performance data for a single rectangular fin and triple fins are provided for different frequency levels (5, 30 and
50HZ) , different input power (5,10,20,30,40 and 50W) and different inlet velocity (0.5, 1, 2, 3, 4, 5 and 6m/s) for the single rectangular fin and triple fins with and without oscillation. The investigation was also performed with different geometrical fin

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Publication Date
Tue Apr 04 2023
Journal Name
International Journal Of Professional Business Review
An Empirical Study to Measure the Impact of Information Technology Governance Under the Control Objectives for Information and Related Technologies on Financial Performance
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Purpose: To determine the effect of information technology governance (ITG) under the control objectives for information and related technologies (COBIT) on financial performance is the objective of this study. Additionally, the article seeks to look into the relationships between the factors under consideration.   Theoretical framework: Information technology and operational processes are evaluated and ensure their compliance with the instructions of the Central Bank of Iraq. Therefore, the research dealt with a conceptual framework by reviewing the literature on the importance of the COBIT framework in assessing financial performance.   Design/methodology/approach: To investigate the effect of information technology; we the valu

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Publication Date
Sun May 02 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Impact of Internal Islamic Certificates of Deposit (ICD) on the Profitability of Islamic Banks: an Empirical Research in Asia-Iraq Islamic Bank
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 As long as Islamic banks cannot operate in an environment that deals with traditional banking instruments based on the interest rate (bank interest) that is prohibited by Article No. (6) of the Islamic Banking Law No. (43) of 2015 which stipulates that (do not deal in any activity that carries Interest (neither taking nor giving)). Therefore it seeks to provide an alternative strategic solution within the framework of the provisions and rules of Islamic Sharia, on the basis of participating in profit and loss to avoid the method of interest taking and giving, to find investment methods to provide new financial products, such as Islamic certificates of deposit and investment funds according to the method Murabaha, speculation (Mudar

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Influence of water-absorbent polymer balls on the structural performance of reinforced concrete beam: An experimental investigation
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Abstract<p>This research investigated the influence of water-absorbent polymer balls (WAPB) on reinforced concrete beams’ structural behavior experimentally. Four self-compacted reinforced concrete beams of identical geometric layouts 150 mm × 200 mm × 1,500 mm, reinforcement details, and compressive strength <inline-formula> <alternatives> <inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_jmbm-2022-0024_eq_001.png"></inline-graphic> <math xmlns:m="http://www.w3.org/1998/Math/MathML"> <msubsup> <mrow> </mrow></msubsup></math></alternatives></inline-formula></p> ... Show More
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Publication Date
Mon Jul 04 2022
Journal Name
Journal Of Petroleum Exploration And Production Technology
Effect of acid treatment on the geomechanical properties of rocks: an experimental investigation in Ahdeb oil field
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Acidizing is one of the most used stimulation techniques in the petroleum industry. Several reports have been issued on the difficulties encountered during the stimulation operation of the Ahdeb oil field, particularly in the development of the Mishrif reservoir, including the following: (1) high injection pressures make it difficult to inject acid into the reservoir formation, and (2) only a few acid jobs have been effective in Ahdeb oil wells, while the bulk of the others has been unsuccessful. The significant failure rate of oil well stimulation in this deposit necessitates more investigations. Thus, we carried out this experimental study to systematically investigate the influence of acid treatment on the geomechanical properties of Mi4

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Publication Date
Fri Jan 01 2016
Journal Name
Procedia Economics And Finance
The Mediating Role of Knowledge Sharing on Relationship between IT Capability and IT Support as Predictors of Innovation Performance: An Empirical Study on Mobile Companies in Iraq
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Publication Date
Tue Mar 08 2022
Journal Name
Multimedia Tools And Applications
Comparison study on the performance of the multi classifiers with hybrid optimal features selection method for medical data diagnosis
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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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