Mubarak Albarka Umar

• Ph.D
• Candidate at United Arab Emirates University

The growing demand for delivering quality software faster “Quality at Speed” requires faster and successful execution of software testing to ensure its standard. Utilizing appropriate testing method(s) and right test automation tools/framework are two defining factors for a successful and effective software testing project. Using one testing method...

One of the key challenges of the machine learning (ML) based intrusion detection system (IDS) is the expensive computation time which is largely caused by the redundant, incomplete, and unrelated features contain in the IDS datasets. To overcome such challenges and ensure building efficient and more accurate IDS models, many researchers utilize pre...

Over the years, insecurity and crime have been significant issues in Nigeria. While the country successfully dealt with the past insecurity challenges conventionally, the government has failed to contain the new insecurity and crime challenges, especially that of the well-known Boko Haram lingering for over a decade now. This is due to various reas...

Intrusion detection systems (IDS) typically take high computational complexity to examine data features and identify intrusion patterns due to the size and nature of the current intrusion detection datasets. Data pre-processing techniques (such as feature selection) are being used to reduce such complex-ity by eliminating irrelevant and redundant f...

The rapid rise of cyberattacks and the limitations of traditional defense systems have prompted the adoption of artificial intelligence (AI) techniques, such as machine learning (ML) and deep learning (DL), to build more efficient and reliable intrusion detection systems (IDSs). However, the advent of larger IDS datasets has introduced challenges r...

Cardiovascular disease (CVD) is a leading cause of death globally. The unpredictability and severity of CVDs, such as sudden cardiac arrests, necessitate real-time monitoring and prediction using the Internet of Things (IoT) and artificial intelligence (AI) for timely intervention. Existing AI models and IoT frameworks for CVD prediction often lack...

The advancement of smart grids has addressed many challenges of traditional power grids, yet it has also introduced new vulnerabilities to cyber-attacks that can disrupt power, leading to severe socio-economic impacts like blackouts and grid disturbance. While numerous supervised machine learning methods have been proposed to detect cyber-attacks i...

Cloud computing and virtualization are fundamental to modern computer system design. As cloud computing adoption grows across organizations, evaluating its performance becomes essential. This study simulates and analyzes a cloud datacenter’s performance using queuing models. Specifically, an Mt/M/1/K queuing system is employed, with arrival paramet...

The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using Machine Learning (ML) techniques to build more efficient and reliable Intrusion Detection Systems (IDSs). However, the advent of larger IDS datasets has negatively impacted the performance and computational complexity of ML-based IDSs....

The growing need for quality software makes software testing a crucial stage in Software Development Lifecycle. There are many techniques of testing software, however, the choice of a technique to test a given software remains a major problem. Although, it is impossible to find all errors in software, selecting the right testing technique can deter...

Due to the size and nature of intrusion detection datasets, intrusion detection systems (IDS) typically take high computational complexity to examine features of data and identify intrusive patterns. Data preprocessing techniques such as feature selection can be used to reduce such complexity by eliminating irrelevant and redundant features in the...

The main function of WEB load balancing is to receive requests sent from clients, and then dynamically allocate requests to the available nodes in the backend. The resources of the backend node server are called according to the rules and policies of the load balancer. Comparing functions, the static load-balancing algorithm is an important part of...

One of the key challenges of machine learning (ML) based intrusion detection system (IDS) is the expensive computational complexity which is largely due to redundant, incomplete, and irrelevant features contain in the IDS datasets. To overcome such challenge and ensure building an efficient and more accurate IDS models, many researchers utilize pre...

Software Testing is the process of evaluating a software program to ensure that it performs its intended purpose. Software testing verifies the safety, reliability, and correct working of software. The growing need for quality software makes software testing a crucial stage in Software Development Lifecycle. There are many methods of testing softwa...

Software Testing is the process of evaluating a software program to ensure that it performs its intended purpose. Software testing verifies the safety, reliability, and correct working of software. The growing need for quality software makes software testing a crucial stage in Software Development Lifecycle. There are many methods of testing softwa...

The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to the use of Machine Learning (ML) techniques to build more efficient and reliable intrusion Detection Systems (IDSs). However, the advent of larger IDS datasets has negatively impacted the performance and computational complexity of ML-based I...

The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to the use of Machine Learning (ML) techniques to build more efficient and reliable intrusion Detection Systems (IDSs). However, the advent of larger IDS datasets has negatively impacted the performance and computational complexity of ML-based I...

The growing need for quality software makes software testing a crucial stage in Software Development Lifecycle. There are many techniques of testing software, however, the choice of a technique to test a given software remains a major problem in software testing. Although, it is impossible to find all errors in software, selecting the right testing...

Fire is as destructive as it is useful. Without a proper pro-active approach to preventing fire outbreaks, the results could be extremely disastrous when they occur. Thus, there is a need for a fast and convenient way of reporting fire incidents. The growing usage of smartphones provides a way of equipping the public with a means of reporting fire...

Abstract - The growing demand for delivering quality software faster “Quality at Speed” requires faster and successful execution of software testing to ensure its standard. Utilizing appropriate testing method(s) and right test automation tools/framework are two defining factors for a successful and effective software testing project. Using one tes...

Software Testing is the process of evaluating a software program to ensure that it performs its intended purpose. Software testing verifies the safety, reliability, and correct working of a software. The growing need for quality software makes software testing a crucial stage in Software Development Lifecycle. There are many methods of testing soft...

Students dropout and delay in graduation are significant problems at Katsina State Institute of Technology and Management (KSITM). There are various reasons for that, students’ performances during first year is one of the major contributing factors. This study aims at predicting poor students’ performances that might lead to dropout or delay in gra...

Outlier detection has always been a more active research topic in statistical diagnosis. Outliers are ubiquitous at data analysis areas in current and may produce erroneous results. In multivariate linear regression model, the existence of outliers will directly affect the modeling, parameter estimation and prediction. A set of data contains abnorm...