Review Of Some Cryptographic Algorithms In Cloud Computing

Alharbi, Mawaddah Fouad,Aldosari, Fahd,Alharbi, Nawaf Fouad International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.9

Cloud computing is one of the most expanding technologies nowadays; it offers many benefits that make it more cost-effective and more reliable in the business. This paper highlights the various benefits of cloud computing and discusses different cryptography algorithms being used to secure communications in cloud computing environments. Moreover, this thesis aims to propose some improvements to enhance the security and safety of cloud computing technologies.

E-Safety Awareness of Saudi Youths: A Comparative Study and Recommendations

Alharbi, Nawaf F,Soh, Ben,AlZain, Mohammed A,Alharbi, Mawaddah F International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.11

The use of the internet has become a basic need for many across the globe. The situation is very much the same for the youth in many countries like Saudi Arabia who have grown up surrounded and accessing the internet. This demographic, however, is at an increased risk of falling as victims to cybercrime because of a low level of technical awareness. This review looks at the level of technical awareness of internet use in 3 different countries which include the USA, South Africa, and New Zealand. The review will compare the situation in these nations with those in KSA. Based on the review and comparisons, recommendations are made for culturally and socially acceptable e-Safety awareness of Saudi youths.

Diagnosing a Child with Autism using Artificial Intelligence

Alharbi, Abdulrahman,Alyami, Hadi,Alenzi, Saleh,Alharbi, Saud,bassfar, Zaid International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.6

Children are the foundation and future of this society and understanding their impressions and behaviors is very important and the child's behavioral problems are a burden on the family and society as well as have a bad impact on the development of the child, and the early diagnosis of these problems helps to solve or mitigate them, and in this research project we aim to understand and know the behaviors of children, through artificial intelligence algorithms that helped solve many complex problems in an automated system, By using this technique to read and analyze the behaviors and feelings of the child by reading the features of the child's face, the movement of the child's body, the method of the child's session and nervous emotions, and by analyzing these factors we can predict the feelings and behaviors of children from grief, tension, happiness and anger as well as determine whether this child has the autism spectrum or not. The scarcity of studies and the privacy of data and its scarcity on these behaviors and feelings limited researchers in the process of analysis and training to the model presented in a set of images, videos and audio recordings that can be connected, this model results in understanding the feelings of children and their behaviors and helps doctors and specialists to understand and know these behaviors and feelings.

Understanding the Risks on Saudi Arabian's Youth Being Online Without Having Strong Cyber-Security Awareness

Alharbi, Nawaf,Soh, Ben,AlZain, Mohammed A,Alharbi, Mawaddah International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.7

The Internet is becoming a basic need for many individuals globally in this digital age. The youths became more active online than before, with the majority relying on different platforms to communicate and interact with peers. Saudi Arabia is one of the nations where internet usage is high, with an increasing number of active internet users. The youth in Saudi Arabia are engaged in various online platforms. However, they lack adequate knowledge about cybersecurity and the dangers of internet usage, which exposes them to the risk of falling victims to cybercriminals. The most common dangers of internet usage include viruses, malware, phishing, and hacking, compromising users' sensitive information. Increased awareness of these potential threats helps protect Internet users and secure their data. The understanding of the dangers of Internet usage among youths varies across countries. In this regard, our study explores the risks of internet usage among youth in Saudi Arabia compared to the United States, South Africa, and New Zealand.

Sustainability Report Publication and Bank Share Price: Evidence from Saudi Arabia Stock Markets

ALHARBI, Mualla Ali,MGAMMAL, Mahfoudh Hussein,AL-MATARI, Ebrahim Mohammed Korea Distribution Science Association 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.2

We examine the effects of the sustainability report (SURE) and investment decision on share price (SPRC). Explore whether the sustainability report changes the value-relevance of financial accounting variables indirectly. It is evident that the number of banks is only 12, which are all banks in Saudi Arabia, and we have included all of them in the final sample. Moreover, the same number of banks applied for the analysis concerning the accounting variables. This article utilizes a panel dataset from a sample of Saudis registered banks from the first quarter of 2014 to the last quarter of 2018. We utilize a balanced sample that contains all banks listed in Tadawul, 240 observations. Run GLM regression to tests the relationships. Findings exhibit that investors value the complementary disclosure of accounting information provided in SURE, and this disclosure produces a positive effect on SPRC. The SURE figure is robustly significant, suggesting that the market assigns a positive-significant correlation to the further information in the SURE. The indirect effects show that BPS×SURE is a positive-significant effect on SPRC, whereas EPS×SURE is positively-insignificant. The analysis shows that SURE's value relevance conforms through Saudis Banks, consistent with the hypothesis that diverse institutional perspectives probably influence the value-relevance of SURE.

An Intelligent Game Theoretic Model With Machine Learning For Online Cybersecurity Risk Management

Alharbi, Talal International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.6

Cyber security and resilience are phrases that describe safeguards of ICTs (information and communication technologies) from cyber-attacks or mitigations of cyber event impacts. The sole purpose of Risk models are detections, analyses, and handling by considering all relevant perceptions of risks. The current research effort has resulted in the development of a new paradigm for safeguarding services offered online which can be utilized by both service providers and users. customers. However, rather of relying on detailed studies, this approach emphasizes task selection and execution that leads to successful risk treatment outcomes. Modelling intelligent CSGs (Cyber Security Games) using MLTs (machine learning techniques) was the focus of this research. By limiting mission risk, CSGs maximize ability of systems to operate unhindered in cyber environments. The suggested framework's main components are the Threat and Risk models. These models are tailored to meet the special characteristics of online services as well as the cyberspace environment. A risk management procedure is included in the framework. Risk scores are computed by combining probabilities of successful attacks with findings of impact models that predict cyber catastrophe consequences. To assess successful attacks, models emulating defense against threats can be used in topologies. CSGs consider widespread interconnectivity of cyber systems which forces defending all multi-step attack paths. In contrast, attackers just need one of the paths to succeed. CSGs are game-theoretic methods for identifying defense measures and reducing risks for systems and probe for maximum cyber risks using game formulations (MiniMax). To detect the impacts, the attacker player creates an attack tree for each state of the game using a modified Extreme Gradient Boosting Decision Tree (that sees numerous compromises ahead). Based on the findings, the proposed model has a high level of security for the web sources used in the experiment.

Designing CuSe-gCN nanocomposite as an active electrocatalyst for water oxidation

Alharbi Fatemah Farraj,Ahmad Zahoor,Chughtai Adeel Hussain,Khosa Rabia Yasmin,Farid Hafiz Muhammad Tahir 한국화학공학회 2023 Korean Journal of Chemical Engineering Vol.40 No.9

CuSe-gCN nanocrystals were premeditated and produced utilizing a simple hydrothermal method. Different analytical techniques well characterized the generated samples. The prepared samples also contain nanocrystals with a vertical shape, decorated with numerous nanoparticles. All characterizations confirm the phase composition of composite CuSe-gCN. The pore size of the N2 adsorption-desorption isotherm also pointed to a mesoporous structure. Furthermore, the combination of distinct morphology nanoparticles embellished on gCN graphitized nanotubes helps to achieve larger current densities and lower starting potentials for the oxygen evolution process. Because of their unique mesoporous structure, the CuSe-gCN catalysts show exceptional electrical conductivity and electrocatalytic activity. Compared to monometallic CuSe and gCN, CuSe-gCN significantly lower overpotential of 208 mV was needed to obtain a current density of 10 mA/cm2. The CuSe-gCN nanocrystals displayed good stability and a low Tafel slope of 35 mV/dec. This research shows that it is possible to use a copper-based selenide with gCN and combine all the beneficial characteristics in a single catalyst system.. Still, it also offers fresh perspectives on the logical proposal and creation of effective electrocatalysts for various applications.

Clinical Efficacy and Possible Applications of Genomics in Lung Cancer

Alharbi, Khalid Khalaf Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.5

The heterogeneous nature of lung cancer has become increasingly apparent since introduction of molecular classification. In general, advanced lung cancer is an aggressive malignancy with a poor prognosis. Activating alterations in several potential driver oncogenic genes have been identified, including EGFR, ROS1 and ALK and understanding of their molecular mechanisms underlying development, progression, and survival of lung cancer has led to the design of personalized treatments that have produced superior clinical outcomes in tumours harbouring these mutations. In light of the tsunami of new biomarkers and targeted agents, next generation sequencing testing strategies will be more appropriate in identifying the patients for each therapy and enabling personalized patients care. The challenge now is how best to interpret the results of these genomic tests, in the context of other clinical data, to optimize treatment choices. In genomic era of cancer treatment, the traditional one-size-fits-all paradigm is being replaced with more effective, personalized oncologic care. This review provides an overview of lung cancer genomics and personalized treatment.

Using a Genetic-Fuzzy Algorithm as a Computer Aided Breast Cancer Diagnostic Tool

Alharbi, Abir,Tchier, F,Rashidi, MM Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.7

Computer-aided diagnosis of breast cancer is an important medical approach. In this research paper, we focus on combining two major methodologies, namely fuzzy base systems and the evolutionary genetic algorithms and on applying them to the Saudi Arabian breast cancer diagnosis database, to aid physicians in obtaining an early-computerized diagnosis and hence prevent the development of cancer through identification and removal or treatment of premalignant abnormalities; early detection can also improve survival and decrease mortality by detecting cancer at an early stage when treatment is more effective. Our hybrid algorithm, the genetic-fuzzy algorithm, has produced optimized systems that attain high classification performance, with simple and readily interpreted rules and with a good degree of confidence.

Deep Learning Based Rumor Detection for Arabic Micro-Text

Alharbi, Shada,Alyoubi, Khaled,Alotaibi, Fahd International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.11

Nowadays microblogs have become the most popular platforms to obtain and spread information. Twitter is one of the most used platforms to share everyday life event. However, rumors and misinformation on Arabic social media platforms has become pervasive which can create inestimable harm to society. Therefore, it is imperative to tackle and study this issue to distinguish the verified information from the unverified ones. There is an increasing interest in rumor detection on microblogs recently, however, it is mostly applied on English language while the work on Arabic language is still ongoing research topic and need more efforts. In this paper, we propose a combined Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) to detect rumors on Twitter dataset. Various experiments were conducted to choose the best hyper-parameters tuning to achieve the best results. Moreover, different neural network models are used to evaluate performance and compare results. Experiments show that the CNN-LSTM model achieved the best accuracy 0.95 and an F1-score of 0.94 which outperform the state-of-the-art methods.