Abul Bashar

Prince Mohammad bin Fahd University · Computer Engineering

The ubiquitous adoption of Android devices has unfortunately brought a surge in malware threats, compromising user data, privacy concerns, and financial and device integrity, to name a few. To combat this, numerous efforts have explored automated botnet detection mechanisms, with anomaly-based approaches leveraging machine learning (ML) gaining att...

PDF has become a major attack vector for delivering malware and compromising systems and networks, due to its popularity and widespread usage across platforms. PDF provides a flexible file structure that facilitates the embedding of different types of content such as JavaScript, encoded streams, images, executable files, etc. This enables attackers...

The threat of malware in the Internet of Things (IoT) is ever-present given that many IoT systems today rely on the Android operating system. There has been a consistent rise in Android malware recently, with new variants adopting sophisticated detection avoidance techniques, including various forms of obfuscation. Hence, there is a need to improve...

One of the most common and challenging medical conditions to deal with in old-aged people is the occurrence of knee osteoarthritis (KOA). Manual diagnosis of this disease involves observing X-ray images of the knee area and classifying it under five grades using the Kellgren–Lawrence (KL) system. This requires the physician’s expertise, suitable ex...

PDF is one of the most popular document file formats due to its flexibility, platform independence and ability to embed different types of content. Over the years, PDF has become a popular attack vector for spreading malware and compromising computer systems. Existing signature-based defense systems have extremely high recall rates, but quickly bec...

The ever-increasing use of mobile phones running the Android OS has created security threats of data breach and botnet-based remote control. To address these challenges, numerous countermeasures have been proposed in the domain of image-based Android Malware Detection (AMD) applying Deep Learning (DL) approaches. This paper proposes, implements and...

Early detection and diagnosis of brain tumors are essential for early intervention and eventually successful treatment plans leading to either a full recovery or an increase in the patient lifespan. However, diagnosis of brain tumors is not an easy task since it requires highly skilled professionals, making this procedure both costly and time-consu...

A democratic election is a crucial event in any country. Therefore, the government of the country is concerned with creating more competitive and fairer elections. This paper discusses the survey and scope of Blockchain technology adoptions in conducting elections. A distributed digital ledger is used in the Blockchain technology that is utilized f...

Wireless sensor networks occupy a prominent role in industrial as well as scientific applications. Lifetime enhancement and coverage are the major factors considered while designing the network. Various research models are evolved by considering the scheduling and routing process to solve the network lifetime issues. However, coverage and connectiv...

The volume of SMS messages sent on a daily basis globally has continued to grow significantly over the past years. Hence, mobile phones are becoming increasingly vulnerable to SMS spam messages, thereby exposing users to the risk of fraud and theft of personal data. Filtering of messages to detect and eliminate SMS spam is now a critical functional...

Author verification of handwritten text is required in several application domains and has drawn a lot of attention within the research community due to its importance. Though, several approaches have been proposed for the text-independent writer verification of handwritten text, none of these have addressed the problem domain where author verifica...

The complexity of brain tissue requires skillful technicians and expert medical doctors to manually analyze and diagnose Glioma brain tumors using multiple Magnetic Resonance (MR) images with multiple modalities. Unfortunately, manual diagnosis suffers from its lengthy process, as well as elevated cost. With this type of cancerous disease, early de...

Malicious botnet applications have become a serious threat and are increasingly incorporating sophisticated detection avoidance techniques. Hence, there is a need for more effective mitigation approaches to combat the rise of Android botnets. Although the use of Machine Learning to detect botnets has been a focus of recent research efforts, several...

Background: The task of identifying a tumor in the brain is a complex problem that requires sophisticated skills and inference mechanisms to accurately locate the tumor region. The complex nature of the brain tissue makes the problem of locating, segmenting, and ultimately classifying Magnetic Resonance (MR) images a complex problem. The aim of th...

Revealing customer satisfaction through big social data has been an interesting research topic in tourism and hospitality. Big data analysis is an effective way to detect customers’ behaviors in their decision-making. This study aims to perform big social data analysis to reveal whether food quality impacts the relationship between hotel performanc...

To enable more effective mitigation of Android botnets, image-based detection approaches offer great promise. Such image-based or visualization methods provide detection solutions that are less reliant on hand-engineered features which require domain knowledge. In this paper we propose Bot-IMG, a framework for visualization and image-based detectio...

It became apparent that mankind has to learn to live with and adapt to COVID-19, especially because the developed vaccines thus far do not prevent the infection but rather just reduce the severity of the symptoms. The manual classification and diagnosis of COVID-19 pneumonia requires specialized personnel and is time consuming and very costly. On t...

The highly competitive nature of manufacturing industries led to several improvements to reduce costs and improve product quality. The modern manufacturing industries integrate several computational and communication technologies for competitive advantage. This paper describes the evolution of manufacturing processes that led to the digitization of...

Lung cancer is second cancer common to men and women as well as it is one of the world's highest cause of death. Reports in recent years have shown that standard X-rays are not effective in diagnosing lung cancer. It has clinically established that low-dose computed tomography (LDCT)-based diagnosis helps to decreases mortality from lung cancer by...

This book presents emerging concepts in data mining, big data analysis, communication, and networking technologies, and discusses the state-of-the-art in data engineering practices to tackle massive data distributions in smart networked environments. It also provides insights into potential data distribution challenges in ubiquitous data-driven net...

The deep learning being a subcategory of the machine learning follows the human instincts of learning by example to produce accurate results. The deep learning performs training to the computer frame work to directly classify the tasks from the documents available either in the form of the text, image, or the sound. Most often the deep learning uti...

Wireless sensor networks (WSNs) have a wide variety of applications in environment monitoring (such as air pollution and fire detection), industrial operations (such as machine surveillance), and precision agriculture. It is an arduous task to manage a large WSN as constant monitoring is required to keep it operational. Mobile robots are used to de...

The concept of IoT-based Smart Cities has gained momentum in recent years. The research in this domain has focused on modeling key characteristics of future smart cities along with exploring their design and implementation aspects from multiple perspectives. There is, however, a lack of research effort to provide a holistic approach towards model...

he practice of Knowledge Management (KM) started more than two decades ago and its importance was realized by the leading organizations. It is now considered as an integral component of any business organization. Globalization has played a significant role in how business is conducted and thus the need of innovative KM grew. The emergence of Inform...

This, paper presents a novel approach towards a comprehensive analysis of various simulation-based tools to test and measure the Cloud Datacenter performance, scalability, robustness and complexity. There are different Cloud Datacenter resources in cloud Computing Infrastructure like Virtual Machine, CPU, RAM, SAN, LAN and WAN topologies. The serve...

This paper presents a novel approach, SmartCrowd, utilizing the Mobile Cloud Computing (MCC) as a platform to find a solution to manage a large human crowd. The proposed solution caters to big crowd management on important Islamic pilgrimages of Hajj and Umrah in the cities of Makkah and Madinah in Saudi Arabia during a fixed time every year. In re...

The ever evolving telecommunication networks in terms of their technology, infrastructure, and supported services have always posed challenges to the network managers to come up with an efficient Network Management System (NMS) for effective network management. The need for automated and efficient management of the current networks, more specifical...

The recent surge in the popularity and usage of Cloud Computing services by both the enterprise and individual consumers has necessitated efficient and proactive management of data center resources which host services having varied characteristics. One of the major issues concerning both the cloud service providers and consumers is the automatic sc...

The recent emphasis on monitoring and managing telecommunication networks in more intelligent and autonomic manner has led to the emergence and popularity of Machine Learning based Network Management Systems. In order to study the behavior and assess the performance of such NMS, it is essential that a suitable modeling and evaluation framework exis...

This paper presents a novel evaluation study of the Cloud Computing technology, with a focused emphasis on the Cloud Storage mechanisms and the way they are affecting the progress of the present Cloud Services. Considering the exponential growth of the user data and its impact on the Cloud Storage infrastructure, this work provides two major contri...

This paper presents a novel evaluation study of various strategies for modeling and simulating cloud computing systems in order to assess their performance. Considering the exponential growth in the deployment of cloud computing systems worldwide and the need for their proper evaluation, this work provides three major contributions through comprehe...

Network Management Systems (NMS) are used to monitor the network and maintain its performance with a prime focus on guaranteeing sustained QoS to the services. However, another aspect that must be given due importance is the energy consumption of the network elements, specially during the off-peak periods. This paper proposes and implements a novel...

The efficient management of networks and the provisioning of services with desired QoS guarantees is a challenge which needs to be addressed through autonomous mechanisms which are intelligent, lightweight and scalable. Recent focus on applying Machine Learning approaches to model the network and service behavioural patterns have proved to be quite...

The advent of IP-based Next Generation Network (NGN) and its guaranteed QoS promise has attracted significant attention from both service providers and subscribers. However, to fulfil the said promise, there is a need to provide effective Call Admission Control (CAC) based QoS provisioning solutions which are autonomous, intelligent and scalable.

The importance of providing guaranteed Quality of Service (QoS) cannot be overemphasised, especially in the NGN environment which supports converged services on a common IP transport network. Call Admission Control (CAC) mechanisms do provide QoS to class-based services in a proactive manner. However, due to the factors of complexity, scale and dyn...

This paper presents a novel framework for Quality of Service (QoS) management based on the supervised learning approach, Bayesian Belief Networks (BBNs). Apart from proposing the conceptual framework, it provides solution to the problem of Call Admission Control (CAC) in the converged IP-based Next Generation Network (NGN). A detailed description o...

Network Management Systems (NMS) are used to monitor the network and along with Operations Support Systems (OSS) maintain the performance with a focus on guaranteeing sustained QoS to the applications and services. One aspect that is given less importance is the energy consumption of the network elements during the off peak periods. This paper look...

The rapid advancement in educational tools experienced over the recent decades has introduced online teaching environments that can facilitate or help develop virtual universities. As more and more students are obtaining free Internet access, we see instructors starting to provide class information, events, lectures, labs, tutorials, etc. on-line....

The ever-evolving nature of telecommunication networks has put enormous pressure on contemporary Network Management Systems (NMSs) to come up with improved functionalities for efficient monitoring, control and management. In such a context, the rapid deployments of Next Generation Networks (NGN) and their management requires intelligent, autonomic...