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A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a new RNA encoding method and ResNet50 Model, where the encoding is done by splitting the training records into different groups. These groups are protocol, service, flag, and digit, and each group is represented by the number of RNA characters that can represent the group's values. The RNA encoding phase converts network traffic records into RNA sequences, allowing for a comprehensive representation of the dataset. The detection model, utilizing the ResNet architecture, effectively tackles training challenges and achieves high detection rates for different attack types. The KDD-Cup99 Dataset is used for both training and testing. The testing dataset includes new attacks that do not appear in the training dataset, which means the system can detect new attacks in the future. The efficiency of the suggested anomaly intrusion detection system is done by calculating the detection rate (DR), false alarm rate (FAR), and accuracy. The achieved DR, FAR, and accuracy are equal to 96.24%, 6.133%, and 95.99%. The experimental results exhibit that the RNA encoding method can improve intrusion detection.

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Publication Date
Fri May 18 2018
Journal Name
Thesis
The Arabian killifish (Aphanius dispar) as a novel model for mycophysiological studies.
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Abstract Candida albicans is a commensal fungal pathogen that grows in yeast and hyphal forms in the human gut. C. albicans causes mucosal and cutaneous diseases that can result in significant mortality following systematic infections and it also exhibits drug resistance. Zebrafish have been an excellent model to investigate C. albicans infections because of their transparency and the availability of many transgenic lines. However, there is a limitation in using zebrafish as a model because the fish embryos cannot survive at 37°C therefore it is not suitable for studying Candida infections at physiological relevant human body temperature. In this thesis, the normal embryonic development of Arabian killifish (A. dispar) is investigated, rev

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Publication Date
Sun Jan 16 2022
Journal Name
Iraqi Journal Of Science
Auto Crop and Recognition for Document Detection Based on its Contents
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An Auto Crop method is used for detection and extraction signature, logo and stamp from the document image. This method improves the performance of security system based on signature, logo and stamp images as well as it is extracted images from the original document image and keeping the content information of cropped images. An Auto Crop method reduces the time cost associated with document contents recognition. This method consists of preprocessing, feature extraction and classification. The HSL color space is used to extract color features from cropped image. The k-Nearest Neighbors (KNN) classifier is used for classification. 

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Publication Date
Mon Apr 15 2024
Journal Name
Journal Of Engineering Science And Technology
Text Steganography Based on Arabic Characters Linguistic Features and Word Shifting Method
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In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn

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Publication Date
Sun Mar 04 2018
Journal Name
Iraqi Journal Of Science
Image Encryption Using DNA Encoding and RC4 Algorithm
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Nowadays, the rapid development of multi-media technology and digital images transmission by the Internet leads the digital images to be exposed to several attacks in the transmission process. Therefore, protection of digital images become increasingly important.

 To this end, an image encryption method that adopts Rivest Cipher (RC4) and Deoxyribonucleic Acid (DNA) encoding to increase the secrecy and randomness of the image without affecting its quality is proposed. The Means Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Coefficient Correlation (CC) and histogram analysis are used as an evaluation metrics to evaluate the performance of the proposed method. The results indicate that the proposed method is secure ag

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Electrical Engineering
A Method Combining Compressive Sensing-Based Method of Moment and LU Decomposition for Solving Monostatic RCS
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Publication Date
Tue Aug 31 2021
Journal Name
Iraqi Journal Of Science
Detection and Identification of Novel Genes from Fungi Isolated from Wastewater
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     The environment in Mosul city is very rich, containing a wide variety of microorganisms which have not been recognised for a long time. Five new fungal genes were identified and registered for the first time in the gene bank. These included Fusarium falciforme 2020-06-MIK-F1 genes for 5.8S rRNA with Accession no. LC555741, Nectriaceae sp. 2020-06-MIK-F2 genes for ITS1 with Accession no. LC555742, Trichoderma asperellum MIK3 genes for 5.8S rRNA with Accession no. LC575020, Penecillum sp. MIK4 genes for 5.8S rRNA with Accession no. LC575021, and Neurospora crassa MIK5 genes for 5.8S rRNA with Accession no. LC575022.   These fungal genes were isolated from wastewater of Khosr river in Mosul city/ Iraq, whi

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Publication Date
Mon Jan 01 2024
Journal Name
Current Chemistry Letters
Synthesis and characterisation of novel metal-organic frameworks (MOFs) based on zirconium and bicinchoninic acid
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Metal-organic frameworks (MOFs) are a relatively new class of materials of unique porous structures and exceptional properties. Currently, more than 110,000 types of MOFs have been reported among the countless possibilities. In this study, we have synthesised a novel MOF using zirconium chloride as the metal source and 4,4'-dicarboxy-2,2'-biquinoline (bicinchoninic acid disodium salt) as the linker, which reacted in N,N-Dimethylformamide (DMF) solvent. Three preparation methods were employed to prepare five types of the MOF, and they were compared to optimize the synthesis conditions. The resulting MOFs, named Zr-BADS, were characterised using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), microscopy, and

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Publication Date
Wed Nov 24 2021
Journal Name
Iraqi Journal Of Science
A proposal of Multimedia Steganography Algorithm based on Improved Least Significant Bit (LSB) Method
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Because of the rapid development and use of the Internet as a communication media emerged to need a high level of security during data transmission and one of these ways is "Steganography". This paper reviews the Least Signification Bit steganography used for embedding text file with related image in gray-scale image. As well as we discuss the bit plane which is divided into eight different images when combination them we get the actual image. The findings of the research was the stego-image is indistinguishable to the naked eye from the original cover image when the value of bit less than four Thus we get to the goal is to cover up the existence of a connection or hidden data. The Peak to Signal Noise Ratio(PSNR) and Mean Square Error (

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Publication Date
Sun Feb 27 2022
Journal Name
Iraqi Journal Of Science
A New Method in Feature Selection based on Deep Reinforcement Learning in Domain Adaptation
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    In data mining and machine learning methods, it is traditionally assumed that training data, test data, and the data that will be processed in the future, should have the same feature space distribution. This is a condition that will not happen in the real world. In order to overcome this challenge, domain adaptation-based methods are used. One of the existing challenges in domain adaptation-based methods is to select the most efficient features so that they can also show the most efficiency in the destination database. In this paper, a new feature selection method based on deep reinforcement learning is proposed. In the proposed method, in order to select the best and most appropriate features, the essential policies

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Publication Date
Tue Feb 01 2022
Journal Name
Civil Engineering Journal
Calibration of a New Concrete Damage Plasticity Theoretical Model Based on Experimental Parameters
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The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop

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