Papers by Obaida M . Al-hazaimeh
International Journal of Computer Networks & Communications (IJCNC), 2024
A 160-bit (20-byte) hash value, sometimes called a message digest, is generated using the SHA-1 (... more A 160-bit (20-byte) hash value, sometimes called a message digest, is generated using the SHA-1 (Secure Hash Algorithm 1) hash function in cryptography. This value is commonly represented as 40 hexadecimal digits. It is a Federal Information Processing Standard in the United States and was developed by the National Security Agency. Although it has been cryptographically cracked, the technique is still in widespread usage. In this work, we conduct a detailed and practical analysis of the SHA-1 algorithm's theoretical elements and show how they have been implemented through the use of several different hash configurations.
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International Journal of Online and Biomedical Engineering (iJOE), 2023
Alzheimer Disease (AD) is the ordinary type of dementia which does not have any proper and effici... more Alzheimer Disease (AD) is the ordinary type of dementia which does not have any proper and efficient medication. Accurate classification and detection of AD helps to diagnose AD in an earlier stage, for that purpose machine learning and deep learning techniques are used in AD detection which observers both normal and abnormal brain and accurately detect AD in an early. For accurate detection of AD, we proposed a novel approach for detecting AD using MRI images. The proposed work includes three processes such as trilevel pre-processing, swin transfer based segmentation, and multi-scale feature pyramid fusion module-based AD detection. In pre-processing, noises are removed from the MRI images using Hybrid KuanFilter and Improved Frost Filter (HKIF) algorithm, the skull stripping is performed by Geodesic Active Contour (GAC) algorithm which removes the non-brain tissues that increases detection accuracy. Here, bias field correction is performed by Expectation-Maximization (EM) algorithm which removes the intensity non-uniformity. After completed pre-processing, we initiate segmentation process using Swin Transformer based Segmentation using Modified U-Net and Generative Adversarial Network (ST-MUNet) algorithm which segments the gray matter, white matter, and cerebrospinal fluid from the brain images by considering cortical thickness, color, texture, and boundary information which increases segmentation accuracy. The simulation of this research is conducted by Matlab R2020a simulation tool, and the performance of this research is evaluated by ADNI dataset in terms of accuracy, specificity, sensitivity, confusion matrix, and positive predictive value.
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International Journal of Online and Biomedical Engineering (iJOE)
Retinopathy is an eye disease caused by diabetes, and early detection and treatment can potential... more Retinopathy is an eye disease caused by diabetes, and early detection and treatment can potentially reduce the risk of blindness in diabetic retinopathy sufferers. Using retinal Fundus images, diabetic retinopathy can be diagnosed, recognized, and treated. In the current state of the art, sensitivity and specificity are lacking. However, there are still a number of problems to be solved in state-of-the-art techniques like performance, accuracy, and being able to identify DR disease effectively with greater accuracy. In this paper, we have developed a new approach based on a combination of image processing and artificial intelligence that will meet the performance criteria for the detection of disease-causing diabetes retinopathy in Fundus images. Automatic detection of diabetic retinopathy has been proposed and has been carried out in several stages. The analysis was carried out in MATLAB using software-based simulation, and the results were then compared with those of expert ophtha...
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Indonesian Journal of Electrical Engineering and Computer Science
Deep learning has effectively solved complicated challenges ranging from large data analytics to ... more Deep learning has effectively solved complicated challenges ranging from large data analytics to human level control and computer vision. However, deep learning has been used to produce software that threatens privacy, democracy, and national security. Deepfake is one of these new applications backed by deep learning. Fake images and movies created by Deepfake algorithms might be difficult for people to tell apart from real ones. This necessitates the development of tools that can automatically detect and evaluate the quality of digital visual media. This paper provides an overview of the algorithms and datasets used to build deepfakes, as well as the approaches presented to detect deepfakes to date. By reviewing the background of deepfakes methods, this paper provides a complete overview of deepfake approaches and promotes the creation of new and more robust strategies to deal with the increasingly complex deepfakes.
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Indonesian Journal of Electrical Engineering and Computer Science, 2022
Deep learning has effectively solved complicated challenges ranging from large data analytics to ... more Deep learning has effectively solved complicated challenges ranging from large data analytics to human level control and computer vision. However, deep learning has been used to produce software that threatens privacy, democracy, and national security. Deepfake is one of these new applications backed by deep learning. Fake images and movies created by Deepfake algorithms might be difficult for people to tell apart from real ones. This necessitates the development of tools that can automatically detect and evaluate the quality of digital visual media. This paper provides an overview of the algorithms and datasets used to build deepfakes, as well as the approaches presented to detect deepfakes to date. By reviewing the background of deepfakes methods, this paper provides a complete overview of deepfake approaches and promotes the creation of new and more robust strategies to deal with the increasingly complex deepfakes.
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Arabic Dialect Identification is the process of identifying the speaker’s dialect based on severa... more Arabic Dialect Identification is the process of identifying the speaker’s dialect based on several features in the corresponding acoustic wave. In this research, machine learning models for detecting Arabic dialects from acoustic wave is proposed using ADI17 corpus with a short duration (i.e., less than 5 seconds) which contains 1717 wave files with a total of 2 hours, 2 minutes, and 11 seconds. The Mel-Frequency Cepstrum Coefficients (MFCC) and Triangular Filter Bank Cepstral Coefficients (TFCC) are used for features extraction from the input acoustic signal. The extracted features represent the speaker’s features matrix which is used for automatic recognition based on K-Nearest Neighbor (KNN), Random Forest (RF), Multi-Layer Perceptron (MLP), and Artificial Neural Networks (ANN). The Experimental results are validated using MFCC features with an accuracy of 76% for KNN, 64% for RF, 41% for ANN, and 34% for the MLP model, while the obtained results using TFCC features were 62% for ...
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Journal of Discrete Mathematical Sciences and Cryptography
There has been a great deal of interest in researching the behavior of chaotic systems over the p... more There has been a great deal of interest in researching the behavior of chaotic systems over the past decade. They are distinguished by their sensitivity to initial conditions, continuous broad-band power spectrum, and similarity to random behavior. Chaos has possible applications in the encryption, compression, and modulation blocks of a digital communication system. The possibility of self-synchronization of chaotic oscillations has spawned a deluge of research on the cryptographic applications of chaos. FAC (Factoring) and CM (Chaotic maps) are used in this research to develop a new signature system (CM). Our system has a higher security level than any other based on a single hard number- theoretic problem since it is extremely unlikely that FAC and CM can be solved effectively at the same time. We further demonstrate that the scheme’s performance involves only minimal operations in signing and validating logarithms, and that it is impervious to attack.
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Journal of Discrete Mathematical Sciences and Cryptography, 2022
There has been a great deal of interest in researching the behavior of chaotic systems over the p... more There has been a great deal of interest in researching the behavior of chaotic systems over the past decade. They are distinguished by their sensitivity to initial conditions, continuous broad-band power spectrum, and similarity to random behavior. Chaos has possible applications in the encryption, compression, and modulation blocks of a digital
communication system. The possibility of self-synchronization of chaotic oscillations has spawned a deluge of research on the cryptographic applications of chaos. FAC (Factoring) and CM (Chaotic maps) are used in this research to develop a new signature system (CM). Our system has a higher security level than any other based on a single hard number-
theoretic problem since it is extremely unlikely that FAC and CM can be solved effectively at the same time. We further demonstrate that the scheme’s performance involves only minimal operations in signing and validating logarithms, and that it is impervious to attack.
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International Journal of Computing Science and Mathematics
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Bulletin of Electrical Engineering and Informatics
Nowadays the security of multimedia data storage and transfer is becoming a major concern. The tr... more Nowadays the security of multimedia data storage and transfer is becoming a major concern. The traditional encryption methods such as DES, AES, 3-DES, and RSA cannot be utilized for multimedia data encryption since multimedia data include an enormous quantity of redundant data, a very large size, and a high correlation of data elements. Chaos-based approaches have the necessary characteristics for dynamic multimedia data encryption. In the context of dynamical systems, chaos is extremely dependent on the initial conditions, non-convergence, non-periodicity, and exhibits a semblance of randomness. Randomness created from completely deterministic systems is a particularly appealing quality in the field of cryptography and information security. Since its inception in the early '90s, chaotic cryptography has seen a number of noteworthy changes. Throughout these years, several scientific breakthroughs have been made. This paper will give an overview of chaos-based cryptography and it...
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Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance... more Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system that can perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic real-time video-based surveillance system which can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment. To develop our system, we have divided the work into three phases: preprocessing phase, abnormal human activity detection phase, and content-based image retrieval phase. For motion object detection, we used the temporal-differencing algorithm and then located the motions region using the Gaussian function. Furthermore, the shape model based on OMEGA equation was used as a filter for the detected objects (i.e., human and non-human). For object activities analysis, we evaluated and analyzed the human activities of the detected objects. We classified the human activities into two groups: normal activities and abnormal activities based on the support vector machine. The machine then provides an automatic warning in case of abnormal human activities. It also embeds a method to retrieve the detected object from the database for object recognition and identification using content-based image retrieval. Finally, a software-based simulation using MATLAB was performed and the results of the conducted experiments showed an excellent surveillance system that can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment with no human intervention.
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Designers' Forum: Design, Automation and Test in Europe Conference and Exhibition, 2005
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International Journal on Electrical Engineering and Informatics, 2021
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In software engineering, the developers in order to recognize which ingredients or fragments of a... more In software engineering, the developers in order to recognize which ingredients or fragments of any software code that put into practice a definite functionality, they utilize Information Retrieval (IR) methods to mechanically spot the code that implement them. The main contribution of this paper is to study and examine the effects of skipping some textual information, namely, the internal documentations from being integrated when performing source code indexing for locating changes process purposes. In this paper, we performed two experiments over three open systems namely Qt, HippoDraw, and KOFFICE. The first experiment is done with counting the internal documentations when preprocessing the software code for locating changes process, while the other one is when skipping it. We used the standard IR measurements, Recall and Precision, and we computed the Wilcoxon signed-rank test to compare and evaluate the results. The experiments results demonstrate that not all internal document...
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Journal of Computer Science, 2020
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International Journal of Machine Learning and Computing, 2019
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Papers by Obaida M . Al-hazaimeh
communication system. The possibility of self-synchronization of chaotic oscillations has spawned a deluge of research on the cryptographic applications of chaos. FAC (Factoring) and CM (Chaotic maps) are used in this research to develop a new signature system (CM). Our system has a higher security level than any other based on a single hard number-
theoretic problem since it is extremely unlikely that FAC and CM can be solved effectively at the same time. We further demonstrate that the scheme’s performance involves only minimal operations in signing and validating logarithms, and that it is impervious to attack.
communication system. The possibility of self-synchronization of chaotic oscillations has spawned a deluge of research on the cryptographic applications of chaos. FAC (Factoring) and CM (Chaotic maps) are used in this research to develop a new signature system (CM). Our system has a higher security level than any other based on a single hard number-
theoretic problem since it is extremely unlikely that FAC and CM can be solved effectively at the same time. We further demonstrate that the scheme’s performance involves only minimal operations in signing and validating logarithms, and that it is impervious to attack.
maps and factoring. When compared to schemes based on a single problem, the proposed scheme has been mathematically demonstrated to be safer. An alternative to conventional key authentication systems, the proposed scheme can help to design a cryptography system that addresses a variety of issues. In contrast, the newly created authentication technique involves only minimal and low-complexity computations, making it incredibly efficient.