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A Low Complexity ML-Based Methods for Malware Classification

Computers, Materials & Continua 2024年第9期80卷 4833-4857页

作者： Mahmoud E.Farfoura Ahmad Alkhatib Deema Mohammed Alsekait mohammad Alshinwan Sahar A.El-Rahman Didi Rosiyadi Diaa salama Abd Elminaam Cybersecurity Department Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan Computer Systems Program-Electrical Engineering Department Faculty of Engineering-ShoubraBenha UniversityCairo11629Egypt Research Center for Artificial Intelligence and Cybersecurity Electronics and Informatics OrganizationNational Research and Innovation Agency(BRIN)KST Samaun SamadikunBandung40135Republic of Indonesia Jadara Research Center Jadara UniversityIrbid21110Jordan MEU Research Unit Middle East UniversityAmman11831Jordan

The article describes a new method for malware classification,based on a Machine Learning(ML)model architecture specifically designed for malware detection,enabling real-time and accurate malware *** an innovative feature dimensionality reduction technique called the Interpolation-based Feature Dimensionality Reduction Technique(IFDRT),the authors have significantly reduced the feature space while retaining critical information necessary for malware *** technique optimizes the model’s performance and reduces computational *** proposed method is demonstrated by applying it to the BODMAS malware dataset,which contains 57,293 malware samples and 77,142 benign samples,each with a 2381-feature *** the IFDRT method,the dataset is transformed,reducing the number of features while maintaining essential data for accurate *** evaluation results show outstanding performance,with an F1 score of 0.984 and a high accuracy of 98.5%using only two reduced *** demonstrates the method’s ability to classify malware samples accurately while minimizing processing *** method allows for improving computational efficiency by reducing the feature space,which decreases the memory and time requirements for training and *** new method’s effectiveness is confirmed by the calculations,which indicate significant improvements in malware classification accuracy and *** research results enhance existing malware detection techniques and can be applied in various cybersecurity applications,including real-timemalware detection on resource-constrained *** and scientific contribution lie in the development of the IFDRT method,which provides a robust and efficient solution for feature reduction in ML-based malware classification,paving the way for more effective and scalable cybersecurity measures.

关键词： Malware detection ML-based models dimensionality reduction feature engineering

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Bullying Among School Students in the UAE Society

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Psychology Research 2019年第2期9卷 45-56页

作者： Ahmad Falah Alomosh salama mohammad alrahoomi Moudi Mohamed Hamad Alshamsi Omaima Daham Shaban Alani University of Sharjah Sharjah UAE Family Development Center/Government of Sharjah Sharjah UAE

The purpose of this study is to research the bullying phenomenon among school students in the UAE society. This is done through showing the extent of prevalence of bullying, the rate of recurrence of bullying incidences, the most widespread forms of bullying among school children in the Emirati society, and finally, the variation with regards to the prevalence and forms of bullying as related to the student’s gender. Therefore, this study aims to probe the prevalence of this phenomenon in schools, and the frequency of bullying cases as well as its forms. For this purpose, a questionnaire was designed and conducted on a sample size of 1,309 students of both genders. The data were later analyzed using descriptive statistical and analytical metrics that are appropriate for the variables’ measurement level, and which achieve the objectives of the study. The study found that a third of the students (33.3%) were involved in bullying incidents. Furthermore, it was found that 14.2% were the party causing the bullying incident, while 19.1% were the party upon which bullying was inflicted. The study also revealed that within school premises the places where bullying was most likely to occur are corridors, and the places which students felt were the least safe are the closed spaces. As for the forms of bullying students are subjected to, offensive name calling or insults came in first place, followed by cyber/online bullying. The young age and smaller size of a student were among the most important motivators for students to bully him/her. It was also found that 32.8% of students who are exposed to bullying respond in a similar manner. The study showed that most of the bullied students (78.4%) know the person doing the bullying, the females being more cognizant of the perpetrator bullying them. Moreover, 40.7% of the students believe that the teachers and other employees are aware of the bullying taking place, female students to a greater extent than males in this regard. In t

关键词： UAE society bullying cyber bullying offensive names school administration

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Use of ultrasonic transient elastography (Fibroscan) in the assessment of hepatic focal lesion stiffness

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Open Journal of Gastroenterology 2013年第2期3卷 107-112页

作者： Mohamed Yousef Aisha Elsharkawy mohammad El Beshlawy Gamal Esmat Zakaria salama Department of Endemic Medicine and Hepatology Faculty of Medicine Cairo University Cairo Egypt

Background and Aim: Hepatic focal lesions differ in their tissue composition and in the degree of stiffness, so our aim was to evaluate the role of Ultrasonic Transient Elastography (Fibroscan) in the measurement of hepatic focal lesions stiffness in order to differentiate hepatocellular carcinoma (HCC) focal lesions from other non HCC focal lesions. Methods: The study was conducted on 34 patients with hepatic focal lesion(s) in the right lobe located near the liver surface and more than or equal4 cmin diameter, detected by imaging studies and diagnosed by CT and histopathology. Stiffness over the focal lesions was measured by the fibroscan. Results: The median value of stiffness was 72.5 kPa over HCC focal lesions, 17.2 kPa over lymphoma focal lesions, 6.5 kPa over metastatic focal lesions and 10.5 kPa over the sarcoidosis focal lesion. Conclusions: Hepatocellular carcinoma focal lesions are much stiffer than lymphoma, metastasis or sarcoidosis focal lesions. Fibroscan may be a useful non-invasive method in the prediction of hepatocellular carcinoma in the future.

关键词： Hepatic Focal Lesions Hepatocellular Carcinoma Fibroscan Stiffness

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