Papers by Mohammed Alatawi
A Data-Driven Artificial Neural Network Approach to Software Project Risk Assessment
IET Software, Dec 18, 2023
International Journal of Computer Networks and Applications
An increasing number of healthcare applications are making use of wireless body sensor networks (... more An increasing number of healthcare applications are making use of wireless body sensor networks (WBSNs). WBSN technology provides a framework that allows for remote physiological monitoring of patients without the use of wired connections in the house. Furthermore, these systems provide real-time data transfer for medical personnel, allowing them to make timely decisions regarding patient care. Despite this, worries remain about patient data being compromised. This research presents a strategy for protecting patient-provider communications by making use of WBSNs. To solve the problem of how to securely store sensitive information on blockchains, a hybrid cryptographic architecture is proposed. The strengths of both public key and symmetric key cryptography are leveraged in my approach. In order to achieve this goal, I have developed a new algorithm by fusing the AES, RSA, and Blowfish algorithms. My experiments have shown that the proposed solution can keep private data safe without affecting its scalability. Using Logi-XGB as a prediction model for attacks, the proposed approach can successfully thwart 99.7 percent of them.
Deep Learning Technique for Fingerprint Recognition
The use of biometric and special measurements Fingerprints, to verify the identity of users have ... more The use of biometric and special measurements Fingerprints, to verify the identity of users have become effective and reliable, knowing that most of the world's institutions cannot do without biometric software and hardware for ease of use and low operating costs. Biometrics is an advanced part of current society. In this study, a system for fingerprint recognition and identification was designed and implemented. This system was mainly depending on the fingerprint minutiae that represent discontinuous regions in ridges. Deep learning in this study was used to perform the matching process between fingerprints, as it allows the machine to learn itself depending on the large volume of datasets. In this project a method for fingerprint recognition using deep learning is presented. By using CNN, training was made on a group of fingerprints belonging to different people. Eight pictures were passed to each person, in different settings, for easy identification afterwards of any fingerprint. The training process was successful, starting with 75, 98 and 100 percent increase by increasing epoch number. The model was also tested and it succeeded in detecting a fingerprint that was passed on to the model.
Journal of Cloud Computing
Because of the existence of Covid-19 and its variants, health monitoring systems have become mand... more Because of the existence of Covid-19 and its variants, health monitoring systems have become mandatory, particularly for critical patients such as neonates. However, the massive volume of real-time data generated by monitoring devices necessitates the use of efficient methods and approaches to respond promptly. A fog-based architecture for IoT healthcare systems tends to provide better services, but it also produces some issues that must be addressed. We present a bidirectional approach to improving real-time data transmission for health monitors by minimizing network latency and usage in this paper. To that end, a simplified approach for large-scale IoT health monitoring systems is devised, which provides a solution for IoT device selection of optimal fog nodes to reduce both communication and processing delays. Additionally, an improved dynamic approach for load balancing and task assignment is also suggested. Embedding the best practices from the IoT, Fog, and Cloud planes, our a...
Deep Learning Technique for Fingerprint Recognition
2022 2nd International Conference on Computing and Information Technology (ICCIT)
The use of biometric and special measurements Fingerprints, to verify the identity of users have ... more The use of biometric and special measurements Fingerprints, to verify the identity of users have become effective and reliable, knowing that most of the world's institutions cannot do without biometric software and hardware for ease of use and low operating costs. Biometrics is an advanced part of current society. In this study, a system for fingerprint recognition and identification was designed and implemented. This system was mainly depending on the fingerprint minutiae that represent discontinuous regions in ridges. Deep learning in this study was used to perform the matching process between fingerprints, as it allows the machine to learn itself depending on the large volume of datasets. In this project a method for fingerprint recognition using deep learning is presented. By using CNN, training was made on a group of fingerprints belonging to different people. Eight pictures were passed to each person, in different settings, for easy identification afterwards of any fingerprint. The training process was successful, starting with 75, 98 and 100 percent increase by increasing epoch number. The model was also tested and it succeeded in detecting a fingerprint that was passed on to the model.
Sensors
The Internet of Things (IoT) has emerged as a fundamental framework for interconnected device com... more The Internet of Things (IoT) has emerged as a fundamental framework for interconnected device communication, representing a relatively new paradigm and the evolution of the Internet into its next phase. Its significance is pronounced in diverse fields, especially healthcare, where it finds applications in scenarios such as medical service tracking. By analyzing patterns in observed parameters, the anticipation of disease types becomes feasible. Stress monitoring with wearable sensors and the Internet of Things (IoT) is a potential application that can enhance wellness and preventative health management. Healthcare professionals have harnessed robust systems incorporating battery-based wearable technology and wireless communication channels to enable cost-effective healthcare monitoring for various medical conditions. Network-connected sensors, whether within living spaces or worn on the body, accumulate data crucial for evaluating patients’ health. The integration of machine learnin...
International Journal of Scientific and Research Publications (IJSRP), 2021
The cutting-edge studies on Automatic Speech Recognition approach have reported exceptional accur... more The cutting-edge studies on Automatic Speech Recognition approach have reported exceptional accuracy rates that are even comparable to human transcribersposing a question if machine has reached human performance. Automatic Speech Recognition can be used as a biometric authentication technique, which is essential in ciphering many applications used. In light of the Arabic language, only few studies have proposed to assess the effectiveness of using Automatic Speech Recognition in Arabic language; therefore, this study aims to implement Arabic speaker recognition using three different algorithms, including (i) Dynamic Time Warping (DTW), (ii) Gaussian mixture model (GMM), and (iii) Support Vector Machine (SVM). To measure the effectiveness of these algorithm in recognizing the Arabic speech, two datasets are used to train and test them, which are: (i) speech agent archive, and (ii) Arabic speech corpus. The results reveled that the DTW outperforms the GMM and SVM in terms of accuracy, precision, recall and fmeasure, as it achieves 95.7%, 96%, and 95%, and 96%, respectively.
Security and Communication Networks
The attacks of cyber are rapidly increasing due to advanced techniques applied by hackers. Furthe... more The attacks of cyber are rapidly increasing due to advanced techniques applied by hackers. Furthermore, cyber security is demanding day by day, as cybercriminals are performing cyberattacks in this digital world. So, designing privacy and security measurements for IoT-based systems is necessary for secure network. Although various techniques of machine learning are applied to achieve the goal of cyber security, but still a lot of work is needed against intrusion detection. Recently, the concept of hybrid learning gives more attention to information security specialists for further improvement against cyber threats. In the proposed framework, a hybrid method of swarm intelligence and evolutionary for feature selection, namely, PSO-GA (PSO-based GA) is applied on dataset named CICIDS-2017 before training the model. The model is evaluated using ELM-BA based on bootstrap resampling to increase the reliability of ELM. This work achieved highest accuracy of 100% on PortScan, Sql injection...
International Journal of Computer Networks and Applications (IJCNA), 2023
An increasing number of healthcare applications are making use of wireless body sensor networks (... more An increasing number of healthcare applications are making use of wireless body sensor networks (WBSNs). WBSN technology provides a framework that allows for remote physiological monitoring of patients without the use of wired connections in the house. Furthermore, these systems provide real-time data transfer for medical personnel, allowing them to make timely decisions regarding patient care. Despite this, worries remain about patient data being compromised. This research presents a strategy for protecting patient-provider communications by making use of WBSNs. To solve the problem of how to securely store sensitive information on blockchains, a hybrid cryptographic architecture is proposed. The strengths of both public key and symmetric key cryptography are leveraged in my approach. In order to achieve this goal, I have developed a new algorithm by fusing the AES, RSA, and Blowfish algorithms. My experiments have shown that the proposed solution can keep private data safe without affecting its scalability. Using Logi-XGB as a prediction model for attacks, the proposed approach can successfully thwart 99.7 percent of them.
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Papers by Mohammed Alatawi