Preferred Language
Articles
/
mBZlrIoBVTCNdQwCaKL4
Performance Evaluation for Four Supervised Classifiers in Internet Traffic Classification
...Show More Authors

Scopus Clarivate Crossref
View Publication
Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
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 t

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Sat Jan 19 2019
Journal Name
Artificial Intelligence Review
Survey on supervised machine learning techniques for automatic text classification
...Show More Authors

View Publication
Scopus (270)
Crossref (238)
Scopus Clarivate Crossref
Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Engineering
Evaluation of Traffic Performance of Ahmed Urabi Square in Baghdad City
...Show More Authors

At present, smooth movement on the roads is a matter which is needed for each user. Many roads, especially in urban areas geometrically improved because of the number of vehicles increase from time to time.

In this research, Highway capacity software, HCS, 2000, will be adopted to determine the effectiveness of roundabout in terms of capacity of roundabout, delay and level of service of roundabout.

The results of the analysis indicated that the Ahmed Urabi roundabout operates under level of service F with an average control delay of 300 seconds per vehicle during the peak hours.

The through movements of Alkarrada- Aljadiriya direction (Major Direction) represent the heaviest traff

... Show More
View Publication Preview PDF
Crossref (5)
Crossref
Publication Date
Fri Dec 01 2017
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Performance Evaluation of UDP, DCCP, SCTP and TFRC for Different Traffic Flow in Wired Networks
...Show More Authors

<p>The demand for internet applications has increased rapidly.  Providing quality of service (QoS) requirements for varied internet application is a challenging task. One important factor that is significantly affected on the QoS service is the transport layer. The transport layer provides end-to-end data transmission across a network. Currently, the most common transport protocols used by internet application are TCP (Transmission Control Protocol) and UDP (User Datagram Protocol). Also, there are recent transport protocols such as DCCP (data congestion control protocol), SCTP (stream congestion transmission protocol), and TFRC (TCP-friendly rate control), which are in the standardization process of Internet Engineering Task

... Show More
View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
...Show More Authors

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

... Show More
View Publication Preview PDF
Scopus (17)
Crossref (14)
Scopus Clarivate Crossref
Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Mobility Models over UDP Traffic Pattern for MANET Using NS-2
...Show More Authors

  The current study presents the simulative study and evaluation of MANET mobility models over UDP traffic pattern to determine the effects of this traffic pattern on mobility models in MANET which is implemented in NS-2.35 according to various performance metri (Throughput, AED (Average End-2-end Delay), drop packets, NRL (Normalize Routing Load) and PDF (Packet Delivery Fraction)) with various parameters such as different velocities, different environment areas, different number of nodes,  different traffic rates, different traffic sources, different pause times and different simulation times .  A routing protocol.…was exploited AODV(Adhoc On demand Distance Vector) and RWP (Random Waypoint), GMM (Gauss Markov Model), RPGM (Refere

... Show More
View Publication Preview PDF
Scopus (3)
Scopus Clarivate Crossref
Publication Date
Tue Feb 27 2024
Journal Name
Tem Journal
Supervised Classification Accuracy Assessment Using Remote Sensing and Geographic Information System
...Show More Authors

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

... Show More
View Publication Preview PDF
Clarivate Crossref
Publication Date
Tue Aug 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
FDPHI: Fast Deep Packet Header Inspection for Data Traffic Classification and Management
...Show More Authors

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

... Show More
View Publication
Scopus (8)
Crossref (5)
Scopus Crossref
Publication Date
Mon Aug 31 2015
Journal Name
Journal Of Theoretical And Applied Information Technology
EXAM QUESTIONS CLASSIFICATION BASED ON BLOOM’S TAXONOMY COGNITIVE LEVEL USING CLASSIFIERS COMBINATION
...Show More Authors

Preview PDF
Scopus (66)
Scopus
Publication Date
Sun Apr 02 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
...Show More Authors

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

... Show More
View Publication
Scopus (4)
Crossref (3)
Scopus Crossref