Preferred Language
Articles
/
WBbCvYoBVTCNdQwCM6Q9
Features Selection for Intrusion Detection System Based on DNA Encoding
...Show More Authors

Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system. A new features selection method is proposed based on DNA encoding and on DNA keys positions. The current system has three phases, the first phase, is called pre-processing phase, which is used to extract the keys and their positions, the second phase is training phase; the main goal of this phase is to select features based on the key positions that gained from pre-processing phase, and the third phase is the testing phase, which classified the network traffic records as either normal or attack by using specific features. The performance is calculated based on the detection rate, false alarm rate, accuracy, and also on the time that include both encoding time and matching time. All these results are based on using two or three keys, and it is evaluated by using two datasets, namely, KDD Cup 99, and NSL-KDD. The achieved detection rate, false alarm rate, accuracy, encoding time, and matching time for all corrected KDD Cup records (311,029 records) by using two and three keys are equal to 96.97, 33.67, 91%, 325, 13 s, and 92.74, 7.41, 92.71%, 325 and 20 s, respectively. The results for detection rate, false alarm rate, accuracy, encoding time, and matching time for all NSL-KDD records (22,544 records) by using two and three keys are equal to 89.34, 28.94, 81.46%, 20, 1 s and 82.93, 11.40, 85.37%, 20 and 1 s, respectively. The proposed system is evaluated and compared with previous systems and these comparisons are done based on encoding time and matching time. The outcomes showed that the detection results of the present system are faster than the previous ones.

Scopus
Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Partial Encryption for Colored Images Based on Face Detection
...Show More Authors

Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
...Show More Authors
Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
View Publication
Scopus (13)
Crossref (9)
Scopus Crossref
Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Review on Hybrid Swarm Algorithms for Feature Selection
...Show More Authors

    Feature selection represents one of the critical processes in machine learning (ML). The fundamental aim of the problem of feature selection is to maintain performance accuracy while reducing the dimension of feature selection. Different approaches were created for classifying the datasets. In a range of optimization problems, swarming techniques produced better outcomes. At the same time, hybrid algorithms have gotten a lot of attention recently when it comes to solving optimization problems. As a result, this study provides a thorough assessment of the literature on feature selection problems using hybrid swarm algorithms that have been developed over time (2018-2021). Lastly, when compared with current feature selection procedu

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Sat Apr 15 2023
Journal Name
Iraqi Journal Of Science
Hand Written Signature Verification based on Geometric and Grid Features
...Show More Authors

The fact that the signature is widely used as a means of personal verification
emphasizes the need for an automatic verification system. Verification can be
performed either Offline or Online based on the application. Offline systems work on
the scanned image of a signature. In this paper an Offline Verification of handwritten
signatures which use set of simple shape based geometric features. The features used
are Mean, Occupancy Ratio, Normalized Area, Center of Gravity, Pixel density,
Standard Deviation and the Density Ratio. Before extracting the features,
preprocessing of a scanned image is necessary to isolate the signature part and to
remove any spurious noise present. Features Extracted for whole signature

... Show More
View Publication Preview PDF
Publication Date
Sat Jul 06 2024
Journal Name
Multimedia Tools And Applications
Text classification based on optimization feature selection methods: a review and future directions
...Show More Authors

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Entropy-Based Feature Selection using Extra Tree Classifier for IoT Security
...Show More Authors

      The Internet of Things (IoT) is a network of devices used for interconnection and data transfer. There is a dramatic increase in IoT attacks due to the lack of security mechanisms. The security mechanisms can be enhanced through the analysis and classification of these attacks. The multi-class classification of IoT botnet attacks (IBA) applied here uses a high-dimensional data set. The high-dimensional data set is a challenge in the classification process due to the requirements of a high number of computational resources. Dimensionality reduction (DR) discards irrelevant information while retaining the imperative bits from this high-dimensional data set. The DR technique proposed here is a classifier-based fe

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Wed Mar 04 2020
Journal Name
Frontiers In Plant Science
Suppression of Arabidopsis Mediator Subunit-Encoding MED18 Confers Broad Resistance Against DNA and RNA Viruses While MED25 Is Required for Virus Defense
...Show More Authors

View Publication
Scopus (5)
Crossref (5)
Scopus Clarivate Crossref
Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Construct an efficient distributed denial of service attack detection system based on data mining techniques
...Show More Authors

<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynami

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Sat Jul 01 2023
Journal Name
International Journal Of Computing And Digital Systems
Human Identification Based on SIFT Features of Hand Image
...Show More Authors

View Publication
Scopus (1)
Scopus Crossref
Publication Date
Sun Apr 01 2018
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Comparison of Three DNA Extraction Methods for Detection Echinococcus granulosus Isolated from Sheep and Cows
...Show More Authors

Background: Hydatosis caused by Echinococcus granulosus dog tap worm is zoonotic infection and economic importance and to public health constitutes a major threat in certain regions of the Middle East. There is an establishment of preventive and control strategy for characterization of E.granulosus in all endemic area which is essential in all molecular studies, to check the DNA of the parasite.
Objective: Our study aimed to obtain the best from three extractions DNA methods from hydatid cyst protoscolecses isolated from sheep in Al-shawlla abattoir in Baghdad.
Subjects and Methods: Three methods were used to extract DNA samples (boiling, crushing and commercial) DNA samples were performed with electrophoreses on 1.3% agarose. Rega

... Show More
View Publication Preview PDF
Crossref