Survey of Algorithms and Techniques Used to Improve the Security of A Public Wi-Fi Network

Aloufi, Hanouf,Alsuwat, Hatim International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.6

The use of public Wi-Fi has increased in recent years with many people like to spend their time outside in malls or café shops which provide public Wi-Fi for their customers. However, since the public Wi-Fi can be accessed from any device the security of public Wi-Fi plays a big role to prevent the stealing of information by an attacker with methods and techniques such as WPA, WPA2 and WPA3. However, it is well known to the attackers that these methods are not difficult to get hacked by the attacker device to take the client precious information. Some researches were done in increasing the security of public Wi-Fi each with their own different technique or algorithm to provide more secure connection to the public Wi-Fi and prevent any unauthorized user to connect to avoid stealing the data of another legal user. Theses research paper are evaluated to learn which method excel in protecting the public Wi-Fi security by giving an analysis to the methods provided by the research paper with comparing the pros and cons of each algorithm. Moreover, the research displays that there are methods to actually provide security to the public Wi-Fi with each being very different in implementation.

Exploring Support Vector Machine Learning for Cloud Computing Workload Prediction

ALOUFI, OMAR International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.10

Cloud computing has been one of the most critical technology in the last few decades. It has been invented for several purposes as an example meeting the user requirements and is to satisfy the needs of the user in simple ways. Since cloud computing has been invented, it had followed the traditional approaches in elasticity, which is the key characteristic of cloud computing. Elasticity is that feature in cloud computing which is seeking to meet the needs of the user's with no interruption at run time. There are traditional approaches to do elasticity which have been conducted for several years and have been done with different modelling of mathematical. Even though mathematical modellings have done a forward step in meeting the user's needs, there is still a lack in the optimisation of elasticity. To optimise the elasticity in the cloud, it could be better to benefit of Machine Learning algorithms to predict upcoming workloads and assign them to the scheduling algorithm which would achieve an excellent provision of the cloud services and would improve the Quality of Service (QoS) and save power consumption. Therefore, this paper aims to investigate the use of machine learning techniques in order to predict the workload of Physical Hosts (PH) on the cloud and their energy consumption. The environment of the cloud will be the school of computing cloud testbed (SoC) which will host the experiments. The experiments will take on real applications with different behaviours, by changing workloads over time. The results of the experiments demonstrate that our machine learning techniques used in scheduling algorithm is able to predict the workload of physical hosts (CPU utilisation) and that would contribute to reducing power consumption by scheduling the upcoming virtual machines to the lowest CPU utilisation in the environment of physical hosts. Additionally, there are a number of tools, which are used and explored in this paper, such as the WEKA tool to train the real data to explore Machine learning algorithms and the Zabbix tool to monitor the power consumption before and after scheduling the virtual machines to physical hosts. Moreover, the methodology of the paper is the agile approach that helps us in achieving our solution and managing our paper effectively.

A Survey on Predicting Workloads and Optimising QoS in the Cloud Computing

Omar F. Aloufi,Karim Djemame,Faisal Saeed,Fahad Ghabban International Journal of Computer ScienceNetwork S 2024 International journal of computer science and netw Vol.24 No.2

This paper presents the concept and characteristics of cloud computing, and it addresses how cloud computing delivers quality of service (QoS) to the end-user. Next, it discusses how to schedule one's workload in the infrastructure using technologies that have recently emerged such as Machine Learning (ML). That is followed by an overview of how ML can be used for resource management. This paper then looks at the primary goal of this project, which is to outline the benefits of using ML to schedule upcoming demands to achieve QoS and conserve energy. In this survey, we reviewed the research related to ML methods for predicting workloads in cloud computing. It also provides information on the approaches to elasticity, while another section discusses the methods of prediction used in previous studies and those that used in this field. The paper concludes with a summary of the literature on predicting workloads and optimising QoS in the cloud computing.

A Review of Concepts, Advantages and Pitfalls of Healthcare Applications in Blockchain Technology

Al-asmari, Aisha M.,Aloufi, Rahaf I.,Alotaibi, Youseef International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.5

Recently, research in blockchain technology has grown in popularity. Most of these researches have pointed out designing and improving conceptual structures to create digital systems that are more secure, accessible, and effective. Although blockchain offers a wide range of advantages, it also has some pitfalls. This research aims to present an understanding of the properties of blockchain, the advantages, pitfalls, and applications based on blockchain technology. To achieve the goal of understanding blockchain technology concepts, a systematic literature review approach was introduced. 93 papers were chosen and reviewed in total. Therefore, this research provides a summary of recent studies that have been published in the field of blockchain. Moreover, we have created concept maps and tables that aid in a deep understanding of blockchain technology concepts and exhibit some of the blockchain applications. In blockchain-based applications, we focused on two areas, namely the Internet of Things (IoT) and healthcare.

Strategic Information Systems Alignment: Alignment of IS/IT with Business Strategy

Issa-Salwe, Abdisalam,Ahmed, Munir,Aloufi, Khalid,Kabir, Muhammad Korea Information Processing Society 2010 Journal of information processing systems Vol.6 No.1

Using information systems effectively requires an understanding of the organisation, management, and the technology shaping the systems. All information systems can be described as organisational and management solutions to challenges posed by the environment. The advances in information systems have affect on our day-to day lives. As the technology is evolving immensely so are the opportunities in a healthy way to prepare the organisation in the competitive advantage environment In order to manage the IS/IT based systems, it is important to have an appropriate strategy that defines the systems and provide means to manage them. Strategic Information Systems Alignment (SISA) is an effective way of developing and maintaining the IS/IT systems that support the business operations. Alignment of the IS/IT plans and the business plans is essential for improved business performance, this research looks at the key features of SISA in the changing business circumstances in Saudi Arabia.

Strategic Information Systems Alignment: Alignment of IS/IT with Business Strategy

Abdisalam Awssa Salwe,Munir Ahmed,Khalid Aloufi,Muhammad Kabir 한국정보처리학회 2010 Journal of information processing systems Vol.6 No.1

Factor Structure, Validity and Reliability of The Teacher Satisfaction Scale (TSS) In Distance-Learning During Covid-19 Crisis: Invariance Across Some Teachers' Characteristics

Almaleki, Deyab A.,Bushnaq, Afrah A.,Altayyari, Basmah A.,Alshumrani, Amenah N.,Aloufi, Ebtesam H.,Alharshan, Najah A.,Almarwani, Ashwaq D.,Al-yami, Abeer A.,Alotaibi, Abeer A.,Alhazmi, Nada A.,Al-Boq International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.7

This study aimed to examine the Factor Structure of the teacher satisfaction scale (TSS) with distance education during the Covid-19 pandemic, as well as affirming the (Factorial Invariance) according to gender variable. It also aimed at identifying the degree of satisfaction according to some demographic variables of the sample. The study population consisted of all teachers in public education and faculty members in higher education in the Kingdom of Saudi Arabia. The (TSS) was applied to a random sample representing the study population consisting of (2399) respondents. The results of the study showed that the scale consists of five main factors, with a reliability value of (0.94). The scale also showed a high degree of construct validity through fit indices of the confirmatory factor analysis. The results have shown a gradual consistency of the measure's invariance that reaches the third level (Scalar-invariance) of the Measurement Invariance across the gender variable. The results also showed that the average response of the study sample on the scale reached (3.74) with a degree of satisfaction, as there are no statistically significant differences between the averages of the study sample responses with respect to the gender variable. While there were statistically significant differences in the averages with respect to the variable of the educational level in favor of the middle school and statistically significant differences in the averages attributed to the years of experience variable in favor of those whose experience is less than (5) years.

Marker-assisted selection for scab resistance and columnar growth habit in inter-varietal population of apple (Malus × domestica)

Rasool Aatifa,Bhat K. M.,Mir M. A.,Sundouri A. S.,ALshamrani Salha Mesfer,Aloufi Abeer S.,El Moneim Diaa Abd,Mansoor Sheikh,정용석 한국식물생명공학회 2024 Plant biotechnology reports Vol.18 No.1

In recent years, there has been significant progress in enhancing the genetic foundation underlying important agricultural traits such as resistance to scab and the development of a columnar growth habit. V. inaequalis is a hemibiotrophic fungus widely distributed in temperate regions where apples are grown on commercial scale. The present investigation was undertaken to identify Vf gene and Co gene, which, respectively, confer resistance against apple scab disease and columnar phenotype in apple cultivar ‘Rosalie’ and introgression of both the genes in commercially important cultivar ‘Fuji’. Polymorphism sur- vey was carried out between the two parents using 22 simple sequence repeat (SSR) and sequence-characterized amplified region (SCAR) markers. The observations revealed that almost 50% hybrids fall in resistant category and 50% in susceptible category. The results of marker-assisted screening confirmed 38 F1s carrying resistance gene for scab while the remain- ing 32 F1 plants were found to be lacking the gene. The 38 genotypically scab-resistant hybrids were selected for further characterization as columnar and non-columnar plants. Based on the selection criteria, 21 individuals were categorized as columnar and the remaining 17 were categorized as non-columnar. The phenotypic screening was followed by screening of F1 s using molecular markers for Co gene. The amplification of Co-specific markers yielded columnar-specific fragments in the population and fitted the expected 1:1 Mendelian ratio. 18 scab-resistant F1 hybrids were found to carry Co gene and the remaining 20 did not possess the gene for columnar growth habit. Gene-specific primers identified in the present study can be directly used for screening large apple germplasm in a short period of time for developing resistant varieties against apple scab as well as varieties with columnar growth habit. Hybrids with verified scab resistance and columnar growth can be swiftly utilized as scab-resistant columnar cultivars.