• International Journal of Computer Science & Network Security
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• 제21권12호
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• pp.85-92
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• 2021

Distance learning for students with intellectual disabilities can prove beneficial, particularly if adjusted to their educational characteristics and needs. This study seeks to identify the views of parents living in Saudi Arabia, regarding the opportunities offered by distance learning for students with intellectual disabilities, alongside their challenges during the Covid-19 pandemic. The research employed qualitative methods using semi-structured interviews with six parents of students with intellectual disabilities. The results revealed a number of both opportunities and challenges, including issues related to the family, in addition, the data highlighted difficulties related to the educational process (i.e. a lack of variety of educational methods) and technical issues related to access to the Internet and the insufficient computer skills of both teachers and students. The findings have several important implications for future practice, including the need for training workshops for parents concerning the online platform, as well as further research to determine students' perspectives of their experiences with distance learning.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.348-352
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• 2022

This study aims to identify the obstacles to using interactive whiteboards for teachers of students with learning disabilities (LDs) in the Makkah region and to delineate any differences in the levels of these obstacles that can be attributed to the study variables: teachers' gender, academic qualifications, age, and years of experience. The researchers applied the descriptive survey approach to a sample of 123 teachers of LD students. To analyze the results, frequencies, averages, standard deviations, and relative weights were calculated. The results of the study indicated that the levels of the obstacles to using interactive whiteboards for teachers of LD students were moderate. No statistically significant differences in the levels of these obstacles were related to the variables of gender or age, whereas significant differences were found based on academic qualifications and years of experience.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.93-102
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• 2021

This study aimed to test method on the accuracy of estimating the items parameters and ability, using the Three Parameter Logistic. To achieve the objectives of the study, an achievement test in chemistry was constructed for third-year secondary school students in the course of "natural sciences". A descriptive approach was employed to conduct the study. The test was applied to a sample of (507) students of the third year of secondary school in the "Natural Sciences Course". The study's results revealed that the (EAP) method showed a higher degree of accuracy in the estimation of the difficulty parameter and the abilities of persons higher than the MML method. There were no statistically significant differences in the accuracy of the parameter estimation of discrimination and guessing regarding the difference of the two methods: (MML) and (EAP).

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.172-180
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• 2022

Crypto-mining malware (known as crypto-jacking) is a novel cyber-attack that exploits the victim's computing resources such as CPU and GPU to generate illegal cryptocurrency. The attacker get benefit from crypto-jacking by using someone else's mining hardware and their electricity power. This research focused on the possibility of detecting the potential crypto-mining malware in an environment by analyzing both static and dynamic approaches of deep learning. The Program Executable (PE) files were utilized with deep learning methods which are Long Short-Term Memory (LSTM). The finding revealed that LTSM outperformed both SVM and RF in static and dynamic approaches with percentage of 98% and 96%, respectively. Future studies will focus on detecting the malware using larger dataset to have more accurate and realistic results.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.127-130
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• 2022

The number of published journals, conferences, and research papers in computer science is increasing rapidly, which has led to a challenge in coming up with new and unique ideas for research. To alleviate the issue, this paper uses artificial neural networks (ANNs) to generate new computer science research ideas. It does so by using a dataset collected from IEEE published journals and conferences to train an ANN model. The results reveal that the model has a 14% success rate in generating usable ideas. The outcome of this paper has implications for helping both new and experienced researchers come up with novel research topics.

• International Journal of Computer Science & Network Security
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• 제22권8호
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• pp.145-152
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• 2022

The current study investigates the effects of an interactive learning environment on EFL students' vocabulary acquisition and reading comprehension skills. The study utilized a quasi-experimental design. The sample consisted of 41 students enrolled in the English program at Umm Al-Qura University studying Reading in EFL course in Summer 2018/2019. The sample was randomly divided into two groups: A control group consisting of 21 students and an experimental group of 20 students. The results revealed statistically significant differences at (α≤ 0.01) between the mean scores of the experimental group and the control group in the posttest of the vocabulary test and the reading comprehension test favoring the experimental group. Finally, the study concluded with a call for more studies on modern technologies in teaching EFL skills in the Saudi context.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.67-74
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• 2022

One type of network security breach is the availability breach, which deprives legitimate users of their right to access services. The Denial of Service (DoS) attack is one way to have this breach, whereas using the Intrusion Detection System (IDS) is the trending way to detect a DoS attack. However, building IDS has two challenges: reducing the false alert and picking up the right dataset to train the IDS model. The survey concluded, in the end, that using a real dataset such as MAWILab or some tools like ID2T that give the researcher the ability to create a custom dataset may enhance the IDS model to handle the network threats, including DoS attacks. In addition to minimizing the rate of the false alert.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.75-82
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• 2022

Medical data is one of the data that must be kept in safe containers, far from intrusion, viewing and modification. With the technological developments in hospital systems and the use of cloud computing, it has become necessary to save, encrypt and even hide data from the eyes of attackers. Medical data includes medical images, whether they are x-ray images of patients or others, or even documents that have been saved in the image format. In this review, we review the latest research and the latest tools and algorithms that are used to protect, encrypt and hide these images, and discuss the most important challenges facing these areas.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.169-174
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• 2022

The study aims to discover the scope of pre-service special education teachers' knowledge and perceptions of using computer technology in teaching students with disabilities from a pre-service teacher (PST) perspective in light of the gender and sub-major variables. The sample consisted of 84 MEd students/pre-service teachers at the Department of Special Education, Faculty of Education, Umm Al-Qura University. The descriptive analytical approach is used due to its relevance to the study. A survey consisting of the participant's basic information section and 12 statements was sent to a set of pre-service teachers. Findings showed that pre-service special education teachers had an overall high knowledge of using computer technology (M=3.93). Findings also indicated that there were no gender- or major-related statistically significant differences (α = 0.05), in pre-service special education students' knowledge and perceptions of using computer technology.

• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.25-32
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• 2022

The current research aims to identify the effectiveness of a training program based on digital stories to develop writing skills for students with learning difficulties. The research sample consisted of (12) students with learning difficulties in the fifth and sixth grades, who were chosen intentionally. The results showed the effectiveness of the program and the maintenance of this improvement over time as results showed that there were statistically significant differences at the level (α = 0.05) between the two measurements, before and after, in favor of the post-measurement. The results also showed that there were no statistically significant differences at the level (α = 0.05) between the post and follow-up measurements on the writing skills scale. This indicates the long-term impact of the program. The researchers recommend the need to expand educational programs' adoption of digital stories to develop the skills of students with learning difficulties.