Blockchain-based adoption framework for authentic land registry system in Malaysia

Land registration systems are very essential for property ownership management. The exited land registry systems are less efficient and time-consuming and expose to human errors. By using blockchain technology, most of the principles of good governance in land administration such as transparency and efficiency can be fulfilled. However, there is a lack of experience in developing blockchain-based land registry systems. This paper proposes a blockchain-based adoption framework for land registry management in Malaysia. It elaborates more on developing a prototype that fulfills the main functions of current land registration by using smart contract functionalities. Also, this paper illustrates the main challenges of adopting this technology such as expertise shortage of software developers, implementation difficulties due to scalability of the land transactions, data sharing with different types of blockchain and lack of security attacks resistance. Therefore, there is a need to form an agreed-upon blockchain development platform that meet such constraints

Mobile intelligent web pre-fetching scheme for cloud computing services in industrial revolution 4.0

Currently the Mobile Cloud Computing (MCC) rapidly development and being important as the amount of consumers retrieving information continues to grow over time. Every day when customers request the information, large data storage must serve large volume data operations. Therefore, to fix the inadequate information storage encountered by some suppliers, intelligent techniques are need. In addition, the worldwide industry has altered in many areas in recent years owing to excellent technological advances. The Industry 4.0 concept has developed in this modern period and afterward has been embraced and examined by both; scholarly and professionals in numerous other progressed nations. Hence, an enhancement Mobile Intelligent Web Pre-fetching Scheme was proposed to offer a management of cloud data storage for users to readily access the information with quickness wherever to prevent the amount of response time during user access the information. This paper examines the challenges of Cloud Computing (CC) innovation in industry 4.0. The intelligent web pre-fetching technique is utilize to upgrade the execution of Cloud Computing (CC) when taking care of information get to by clients. An improvement of the MCC scheme is propose to bolster information administration to provide proficient and viable execution of MCC services for industry 4.0

Scalability of mobile cloud storage

Today, there are high demands on Mobile Cloud Storage (MCS) services that need to manage the increasing number of works with stable performance. This situation brings a challenge for data management systems because when the number of works increased MCS needs to manage the data wisely to avoid latency occur. If latency occurs it will slow down the data performance and it should avoid that problem when using MCS. Moreover, MCS should provide users access to data faster and correctly. Hence, the research focuses on the scalability of mobile cloud data storage management, which is study the scalable on how deep the data folder itself that increase the number of works

COVID-19 tracking applications acceptance among general populace: an overview in Malaysia

The COVID-19 pandemic forced governments to implement strategies for contact tracing due to the disease’s ease of spread. The Malaysian government has sought to develop and implement a digital contact-tracking application to make it easier and faster to detect the spread; the system has become an integral part of the exit strategy from mandated lockdowns. These applications keep track of the user’s proximity with others who are in the system to inform them early on if they are at a risk of infection. The effectiveness of these applications depends on the willingness of users to install and allow the application to track their location at all times. Therefore, this research aims to identify the factors that would stimulate or slow down the adoption of contact-tracing apps

Cloud-Based DDoS HTTP Attack Detection Using Covariance Matrix Approach

In this era of technology, cloud computing technology has become essential part of the IT services used the daily life. In this regard, website hosting services are gradually moving to the cloud. This adds new valued feature to the cloud-based websites and at the same time introduces new threats for such services. DDoS attack is one such serious threat. Covariance matrix approach is used in this article to detect such attacks. The results were encouraging, according to confusion matrix and ROC descriptors

Extending the unified theory of acceptance and use of technology for COVID-19 contact tracing application by Malaysian users

The Malaysian government has mobilized its strength to confront the current COVID-19 pandemic and has sought to develop and implement a digital contact tracking application, making it an integral part of the exit strategy from the lockdown. These applications record which users have been near one another. When a user is confirmed with COVID-19, app users who have recently been near this person are notified. The effectiveness of these applications is determined by the users’ willingness to install and use them. Therefore, this research aims at identifying the factors that would stimulate or slow down the adoption of a contact-tracing app. It proposes solutions to mitigate the impact of the factors affecting the user’s acceptance of COVID-19 Digital Contact Tracing Apps. A quantitative approach was followed in this research, where an electronic survey was spread in Malaysia, for the objective of data collection, considering the previous discussion of the results. Then, using PLS-SEM, the collected data were analyzed statistically. The findings of this study indicate that the unified theory of acceptance and use of technology (UTAUT) factors (Performance Expectancy, Effort Expectancy, Social Influence, Facilities Condition) were significant predictors of MySejahtera application adoption among citizens in Malaysia. On the other hand, the factors of app-related privacy concern were found to be insignificant for MySejahtera application adoption. View Full-Tex

An extended oversampling method for imbalanced Quranic text classification based on a genetic algorithm

The Quran is considered the holy book for the Muslim community, and its text contains vast amounts of knowledge and guidance that Muslims strive to extract and understand. To achieve this, Quranic text classification plays a crucial role in categorizing and organizing the vast amount of information contained within the Quranic text. However, the process of Quranic text classification is not without its challenges. One of the significant challenges in Quranic text classification is obtaining a homogenous and balanced dataset to train the classification models accurately. Due to the nature of the Quranic text, which contains various topics and themes, the distribution of Quranic text classes is often abnormal. This abnormal distribution makes it difficult to obtain a consistent and balanced dataset, which can weaken the overall classification performance. To address this issue, this paper proposes a new oversampling method that employs Genetic algorithm to generate an optimal and balanced dataset simultaneously. The proposed method is specifically tested for Quranic topics that contain several imbalanced binary classes. The results of the study demonstrate the effectiveness of the Genetic algorithm in generating a balanced dataset, which leads to better classification performance results. Overall, this paper highlights the importance of Quranic text classification and the challenges associated with it. The proposed oversampling method provides a novel solution to address the issue of imbalanced Quranic datasets and can significantly improve the accuracy of Quranic text classification

Blockchain-based adoption framework for authentic land registry system in Malaysia

open access article This research is funded by UniKL/CoRI/str19045. Very great appreciation to UniKl and University of Science and Technology (Yemen) for their unlimited support.Land registration systems are very essential for property ownership management. The exited land registry systems are less efficient and time-consuming and expose to human errors. By using blockchain technology, most of the principles of good governance in land administration such as transparency and efficiency can be fulfilled. However, there is a lack of experience in developing blockchain-based land registry systems. This paper proposes a blockchain-based adoption framework for land registry management in Malaysia. It elaborates more on developing a prototype that fulfills the main functions of current land registration by using smart contract functionalities. Also, this paper illustrates the main challenges of adopting this technology such as expertise shortage of software developers, implementation difficulties due to scalability of the land transactions, data sharing with different types of blockchain and lack of security attacks resistance. Therefore, there is a need to form an agreed-upon blockchain development platform that meet such constraints

Scalability of Mobile Cloud Storage

Today, there are high demands on Mobile Cloud Storage (MCS) services that need to manage the increasing number of works with stable performance. This situation brings a challenge for data management systems because when the number of works increased MCS needs to manage the data wisely to avoid latency occur. If latency occurs it will slow down the data performance and it should avoid that problem when using MCS. Moreover, MCS should provide users access to data faster and correctly. Hence, the research focuses on the scalability of mobile cloud data storage management, which is study the scalable on how deep the data folder itself that increase the number of works

Exploring Critical Challenges and Factors Influencing E-Learning Systems Security During COVID-19 Pandemic

The COVID-19 pandemic swiftly forced the closure of higher education institutions across the world. As a result, all educational institutions have made a considerable move toward e-learning. E-learning systems suffer from confidentiality, integrity, and availability-related security threats. Hence, understanding this problem from various perspectives that include technology, human behavior, management, and policies, as well as implementing policies and standards will assist in finding the most influencing factors that can help in protecting e-learning information systems from potential security threats. In this research, a review has been conducted to analyze and assess 55 states of the art articles on e-learning security and to identify countermeasures to strengthen e-learning information systems. The study contributes to our understanding of how to strengthen the e-learning information systems security by answering the following questions: What are the factors that have an impact on the e-learning systems vulnerability during the COVID-19 pandemic? What are the most important technology, management, and environment-based factors that need to be considered for protecting e-learning systems from potential security attacks?. The results of this study will enable decision and policymakers at higher education institutions to better understand the essential elements of adopting an e-learning system. Knowing these factors will help the designers and developers of e-learning systems adopt secure software design and development methodologies to reduce the likelihood that such vulnerabilities and it contributes to enhancing the system's security resilience against potential attacks. In addition, university management will be more knowledgeable about how to instruct their staff and students on best practices for using e-learning web applications