Browsing by Author "Al-Othmani, Abdulaleem"

Now showing 1 - 11 of 11
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    Blockchain-based adoption framework for authentic land registry system in Malaysia
    (Universitas Ahmad Dahlan, 2021-12-01) Aborujilah, Abdulaziz; Mohd Yatim, Muhammad Naqib bin; Al-Othmani, Abdulaleem
    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.
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    CIA-based Analysis for E-Learning Systems Threats and Countermeasures in Malaysian Higher Education: Review Paper
    (IEEE, 2023-02-08) Aborujilah, Abdulaziz; Adamu, Jibril; Mokhtar, Shamsul Anuar; Al-Othmani, Abdulaleem; Al-alwi, Elham Yahya; Al-Hidabi, Dawood Abdulmalek Yahya
    In Malaysia, the early days of e-learning implementations can be traced back to the late 1990s. However, the development and use of such systems are fraught with security issues, concerns about the security of personal data, and content-related security flaws, confidentiality, integrity, availability, authentication, and deliberate attacks are the list of security issues that are identified in the e-learning systems. More attention has been given to course creation and delivery and technology adoption. However, user privacy and security in the context of e-learning security have not been studied well. In this paper, an in-depth review has been conducted regarding security threats and their remedies to the e-learning systems, which consequently lead Malaysia's higher education to take precautionary measures to facilitate learners with a secure learning environment.
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    Comparative Study of SMOTE and Bootstrapping Performance Based on Predication Methods
    (Springer, 2021-05-06) Aborujilah, Abdulaziz; Nassr, Rasheed Mohammad; Al-Hadhrami, Tawfik; Husen, Mohd Nizam; Ali, Nor Azlina; Al-Othmani, Abdulaleem; Hamdi, Mustapha
    Recently, there has been a renewed interest in smart health systems that aim to deliver high quality healthcare services. Prediction methods are very essential to support these systems. They mainly rely on datasets with assumptions that match the reality. However, one of the greatest challenges to prediction methods is to have datasets which are normally distributed. This paper presents an experimental work to implement SMOTE (Synthetic Minority Oversampling Technique) and bootstrapping methods to normalize datasets. It also measured the impact of both methods in the performance of different prediction methods such as Support vector machine (SVM), Naive Bayes, and neural network(NN) The results showed that bootstrapping with native bays yielded better prediction performance as compared to other prediction methods with SMOTE.
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    Conceptual Model for Automating GDPR Compliance Verification Using Natural Language Approach
    (IEEE, 2022-12-28) Aborujilah, Abdulaziz; Al-Othmani, Abdulaleem; Awang Long, Zalizah; Hussien, Nur Syahela; Abdul Ghani, Dahlan
    Most mobile apps require regular access to sensitive personal information. Regulators are increasingly demanding mobile app makers disclose privacy policies that detail what users’ data is gathered and used. Compliance with data privacy and protection regulations must be monitored to reduce legal penalties that may come from unexpected data breaches. Checking and verifying The General Data Protection Regulation (GDPR) Compliance is quite a challenging issue. In this paper, we propose, an extension to be added to the automated GDPR compliance verification tool. This extension shows how the questions about the compliance of mobile applications might be answered based on GDPR standards. The implementation phases of the extension are explained. It includes query processing, document retrieval, passage retrieval, and answer extraction. This paper provides mobile application developers with a better technique of how to monitor users' compliance with mobile application privacy policies.
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    Cybersecurity Risk Assessment Approach for Malaysian Organizations: Malaysian Universities as Case Study
    (IEEE, 2022-05-16) Aborujiah, Abdulaziz; Al-Othmani, Abdulaleem; Hussien, Nur Syahela; Mokhtar, Shamsul Anuar; Awang Long, Zalizah; Husen, Mohd Nizam
    Malaysian organizations are following different methods for cybersecurity risk assessment such as Control Objectives for Information and Related Technologies (COBIT) and International Organization for Standardization (ISO) 27001. The higher education institutions in Malaysia are facing the same difficulties as different standards and approaches are used to evaluate the cybersecurity risk of their institutions. So, there is a lack of a cybersecurity risk assessment approach that takes Malaysian and international standards into consideration. This paper aims to develop a cybersecurity risk assessment approach for higher education institutions in Malaysia. The methodology of conducting this research is qualitative research using a case study. The framework has considered international cybersecurity standards such as the Holistic cybersecurity maturity assessment framework (HCYMAF) and local cybersecurity standards such as National Cyber Security Agency (NACSA) and the Malaysia Cyber Security Strategy (MCSS). In addition, a measurable instrument to assess cybersecurity risk has been proposed. The subject-matter expert can apply this approach to assess their organization's cybersecurity maturity and risk. The findings of this study shall be useful in overcoming the drawbacks of employing non-standard procedures in such evaluations, resulting in more accurate and reliable evaluation outcomes.
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    Empirical Analysis for Stock Price Prediction Using NARX Model with Exogenous Technical Indicators
    (Hindawi, 2022-03-25) Dhafer, Ali H.; Mat Nor, Fauzias; Alkawsi, Gamal; Al-Othmani, Abdulaleem; Ridzwan Shah, Nuradli; Alshanbari, Huda M.; Khairi, Khairil Faizal; Baashar, Yahia
    Stock price prediction is one of the major challenges for investors who participate in the stock markets. Therefore, different methods have been explored by practitioners and academicians to predict stock price movement. Artificial intelligence models are one of the methods that attracted many researchers in the field of financial prediction in the stock market. This study investigates the prediction of the daily stock prices for Commerce International Merchant Bankers (CIMB) using technical indicators in a NARX neural network model. The methodology employs comprehensive parameter trails for different combinations of input variables and different neural network designs. The study seeks to investigate the optimal artificial neural networks (ANN) parameters and settings that enhance the performance of the NARX model. Therefore, extensive parameter trails were studied for various combinations of input variables and NARX neural network configurations. The proposed model is further enhanced by preprocessing and optimising the NARX model’s input and output parameters. The prediction performance is assessed based on the mean squared error (MSE), R-squared, and hit rate. The performance of the proposed model is compared with other models, and it is shown that the utilisation of technical indicators with the NARX neural network improves the accuracy of one-step-ahead prediction for CIMB stock in Malaysia. The performance of the proposed model is further improved by optimising the input data and neural network parameters. The improved prediction of stock prices could help investors increase their returns from investment in stock markets.
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    Exploring Critical Challenges and Factors Influencing E-Learning Systems Security During COVID-19 Pandemic
    (IEEE, 2022-12-28) Aborujilah, Abdulaziz; Al-Alawi, Elham Yahya; Al-Hidabi, Dawood Abdulmalek; Al-Othmani, Abdulaleem
    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.
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    A Fingerprint Authentication for Android-Based Healthcare Appointment Scheduling System
    (International Journal of Current Research and Review, 2021-06-22) Al-Shujaa, Abdulmalek; Nabi, MS; Al-Maatouk, Qusay; Al-Othmani, Abdulaleem
    Introduction: Healthcare organizations maintain patient sensitive data that requires to comply with privacy and security laws. At the same time should provide a system with ease of access. Objective: The main purpose of this research is to develop a mobile application that can manage, and control patients flow at the healthcare by allowing the doctor to upload their appointments and then allow clients (patients) to book one of the available slots in an efficient and effective way. Methods: A survey has been conducted on 100 android app users in Malaysia, it has been observed that businesses’ owners does not trust current mobile appointment applications and prefer to use the traditional methods, which is on first come, first serve bases. Aside from that, current issues that are faced by the users are that most of the mobile appointment applications are unsecured and there is no security control over the account holders for these applications. Results: The developed application also includes extra feature such as secure chatting function that links between the users of the app and let them discuss any type of inquiries related to the booked appointment. AES, SHA-256 and SCRYPTE algorithm has been implemented successfully on the developed application and hence will increase the layer of security and keep user data in a safe manner. AES encryption used to encrypt the users chatting messages while the SHA-256 used to hash the secret key that used to encrypt and decrypt data. Moreover, Conclusion: Biometric fingerprint authentication has integrated with the system in order to solve the existing security flaws of the current appointment applications as well as email verification for avoiding the anonymous user and increase the overall security features.
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    IoT Forensics: Current Perspectives and Future Directions
    (MDPI, 2024-08-12) Ahmed, Abdulghani Ali; Farhan, Khalid; Jabbar, Waheb A.; Al-Othmani, Abdulaleem; Abdulrahman, Abdullahi Gara
    The Internet of Things forensics is a specialised field within digital forensics that focuses on the identification of security incidents, as well as the collection and analysis of evidence with the aim of preventing future attacks on IoT networks. IoT forensics differs from other digital forensic fields due to the unique characteristics of IoT devices, such as limited processing power and connectivity. Although numerous studies are available on IoT forensics, the field is rapidly evolving, and comprehensive surveys are needed to keep up with new developments, emerging threats, and evolving best practices. In this respect, this paper aims to review the state of the art in IoT forensics and discuss the challenges in current investigation techniques. A qualitative analysis of related reviews in the field of IoT forensics has been conducted, identifying key issues and assessing primary obstacles. Despite the variety of topics and approaches, common issues emerge. The majority of these issues are related to the collection and pre-processing of evidence because of the counter-analysis techniques and challenges associated with gathering data from devices and the cloud. Our analysis extends beyond technological problems; it further identifies the procedural problems with preparedness, reporting, and presentation as well as ethical issues. In particular, it provides insights into emerging threats and challenges in IoT forensics, increases awareness and understanding of the importance of IoT forensics in preventing cybercrimes, and ensures the security and privacy of IoT devices and networks. Our findings make a substantial contribution to the field of IoT forensics, as they not only involve a critical analysis of the challenges presented in existing works but also identify numerous problems. These insights will greatly assist researchers in identifying appropriate directions for their future research. d
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    Post Acceptance Model for Online Teleconsultation services: An Empirical Study in Malaysia
    (J.J. Strossmayer, University of Osijek, 2021-11-02) Aborujiah, Abdulaziz; Nassr, Rasheed Mohammad; Al-Othmani, Abdulaleem; Awang Long, Zalizah; Husen, Mohd Nizam
    Most nations across the world are actively pursuing equal access to healthcare services. Teleconsultation technology is a substantial improvement in terms of an effective framework for the provision of healthcare services. However, a lack of understanding of people’s willingness towards the use of this technology has been observed. The goal of this study is to investigate the factors affecting the post-acceptance of teleconsultation services in Malaysia. This study developed a theoretical model which involves the combination of the second generation of Unified Theory of Acceptance and Use of Technology (UTAUT2) and Expectation Confirmation Theory (ECT), with the inclusion of several other constructs. An online survey was used to collect data from 154 university students and partial least squares (PLS) approach was used for data analysis. The research findings indicate that confirmation, performance, effort expectancy, usefulness, and satisfaction were the key factors that affect the post-acceptance of teleconsultation services. Furthermore, actual use, ease of use, technology readiness, and facilitating conditions did not impact participants' post intention in the continuous usage of teleconsultation facilities.
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    Secured Software Embedded System Against Data Breaches on Automotive Industry
    (IAEME, 2020-11-11) Kurniawan, Denny; Alrashdan, Maen T.; Al-Maatouk, Qusay; Al-Othmani, Abdulaleem
    Automotive industry especially in global economy is facing a security threat especially on data breach. Research has shown that this data breach is happening due to advanced our technologies that turned car into primary targets for cyberattack especially on data breach as system protection became vulnerable due to lack of protection on the car itself, it will become the main source of the target for hackers to gain data from user and use it for their own benefits. This study aims to propose a system that protects user privacy and against data breaches. As it will build upon the existing system, it will ask: What will be the impact of this new implemented system fare against the old system? In this context, Data breach is a security incident where information can be gained without user agreement as it can be used for profits or identity theft. Based on the literature review, questionnaire will be used to the users to answer the question related the proposed system and the old system. The results of this will be indicating whether user know the system that has been on their car or not while also this result will be used for analysis on the proposed system. Further research will be needed to be conducted to further improve the proposed system as it could be increasing the effectiveness.