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Fulltext Model for successful development and implementation of Cyber Security Operations Centre (SOC)

Abd Majid M, Zainol Ariffin KA

PLoS One, 2021;16(11):e0260157.
PMID: 34797896 DOI: 10.1371/journal.pone.0260157

Cyberattacks have changed dramatically and have become highly advanced. This latest phenomenon has a massive negative impact on organizations, such as financial losses and shutting-down of operations. Therefore, developing and implementing the Cyber Security Operations Centre (SOC) is imperative and timely. Based on previous research, there are no international guidelines and standards used by organizations that can contribute to the successful implementation and development of SOC. In this regard, this study focuses on highlighting the significant factors that will impact and contribute to the success of SOC. Simultaneously, it will further design a model for the successful development and implementation of SOC for the organization. The study was conducted quantitatively and involved 63 respondents from 25 ministries and agencies in Malaysia. The results of this study will enable the retrieval of ten success factors for SOC, and it specifically focuses on humans, processes, and technology. The descriptive analysis shows that the top management support factor is the most influential factor in the success of the development and implementation of SOC. The study also contributes to the empirical finding that technology and process factors are more significant in the success of SOCs. Based on the regression test, the technology factor has major impact on determining the success of SOC, followed by the process and human factors. Relevant organizations or agencies can use the proposed model to develop and implement SOCs, formulate policies and guidelines, strengthen human models, and enhance cyber security.
Fulltext Geographic information systems adoption model: A partial least square-structural equation modeling analysis approach

Alzahrani NA, Sheikh Abdullah SNH, Adnan N, Zainol Ariffin KA, Mukred M, Mohamed I, et al.

Heliyon, 2024 Aug 15;10(15):e35039.
PMID: 39170420 DOI: 10.1016/j.heliyon.2024.e35039

The ability of Geographic Information System (GIS) to organize, analyze, visualize and integrate spatial data has been at the top of its primary uses among professional industries. However, considering the extensive adoption of Information System (IS) throughout history for government organizations' or citizens' disaster response, the implementation of geographical elements is still minimal. Previous GIS models and framework studies, particularly in developing countries, were affected by pandemic pressure, competitiveness pressure, change management, and security factors. Thus, this study aims to develop a model for the successful adoption of GIS using the Technology Acceptance Model (TAM), and De Lone and Mc Lean Information Success Model and analyze the applicability of the existing factors to enhance the performance of Public Sector Organizations (PSOs). From the study, a new conceptual framework was proposed to examine the effects of factors on GIS adoption that impact performance among PSOs from the perspective of Saudi Arabia. Quantitative methods were used to collect data through a questionnaire distributed to 350 respondents from PSO, and only 272 were found to be valid. Partial Least Square Structural Equation Modeling (PLS-SEM) validated the GIS model. The finding revealed that system quality, service quality, change management, competitiveness pressure, perceived ease of use, perceived usefulness, and security factors significantly and positively affected GIS adoption. The study also showed that GIS adoption substantially affected PSO performance. The proposed model provides insight into how GIS adoption can eventually enhance performance among PSOs. In essence, the study contributes to the running of PSO and the decisions taken by policymakers.
Federated learning for millimeter-wave spectrum in 6G networks: applications, challenges, way forward and open research issues

Qamar F, Kazmi SHA, Siddiqui MUA, Hassan R, Zainol Ariffin KA

PeerJ Comput Sci, 2024;10:e2360.
PMID: 39650377 DOI: 10.7717/peerj-cs.2360

The emergence of 6G networks promises ultra-high data rates and unprecedented connectivity. However, the effective utilization of the millimeter-wave (mmWave) as a critical enabler of foreseen potential in 6G, poses significant challenges due to its unique propagation characteristics and security concerns. Deep learning (DL)/machine learning (ML) based approaches emerged as potential solutions; however, DL/ML contains centralization and data privacy issues. Therefore, federated learning (FL), an innovative decentralized DL/ML paradigm, offers a promising avenue to tackle these challenges by enabling collaborative model training across distributed devices while preserving data privacy. After a comprehensive exploration of FL enabled 6G networks, this review identifies the specific applications of mmWave communications in the context of FL enabled 6G networks. Thereby, this article discusses particular challenges faced in the adaption of FL enabled mmWave communication in 6G; including bandwidth consumption, power consumption and synchronization requirements. In view of the identified challenges, this study proposed a way forward called Federated Energy-Aware Dynamic Synchronization with Bandwidth-Optimization (FEADSBO). Moreover, this review highlights pertinent open research issues by synthesizing current advancements and research efforts. Through this review, we provide a roadmap to harness the synergies between FL and mmWave, offering insights to reshape the landscape of 6G networks.
Fulltext A Geospatial Drug Abuse Risk Assessment and Monitoring Dashboard Tailored for School Students: Development Study With Requirement Analysis and Acceptance Evaluation

Al-Aboosi AM, Sheikh Abdullah SNH, Ismail R, Abdul Maulud KN, Nahar L, Zainol Ariffin KA, et al.

JMIR Hum Factors, 2024 Jul 30;11:e48139.
PMID: 39078685 DOI: 10.2196/48139

BACKGROUND: The enormous consequences of drugs include suicides, traffic accidents, and violence, affecting the individual, family, society, and country. Therefore, it is necessary to constantly identify and monitor the drug abuse rate among school-going youth. A geospatial dashboard is vital for the monitoring of drug abuse and related crime incidence in a decision support system.
OBJECTIVE: This paper mainly focuses on developing MyAsriGeo, a geospatial drug abuse risk assessment and monitoring dashboard tailored for school students. It introduces innovative functionality, seamlessly orchestrating the assessment of drug abuse usage patterns and risks using multivariate student data.
METHODS: A geospatial drug abuse dashboard for monitoring and analysis was designed and developed in this study based on agile methodology and prototyping. Using focus group and interviews, we first examined and gathered the requirements, feedback, and user approval of the MyAsriGeo dashboard. Experts and stakeholders such as the National Anti-Drugs Agency, police, the Federal Department of Town and Country Planning, school instructors, students, and researchers were among those who responded. A total of 20 specialists were involved in the requirement analysis and acceptance evaluation of the pilot and final version of the dashboard. The evaluation sought to identify various user acceptance aspects, such as ease of use and usefulness, for both the pilot and final versions, and 2 additional factors based on the Post-Study System Usability Questionnaire and Task-Technology Fit models were enlisted to assess the interface quality and dashboard sufficiency for the final version.
RESULTS: The MyAsriGeo geospatial dashboard was designed to meet the needs of all user types, as identified through a requirement gathering process. It includes several key functions, such as a geospatial map that shows the locations of high-risk areas for drug abuse, data on drug abuse among students, tools for assessing the risk of drug abuse in different areas, demographic information, and a self-problem test. It also includes the Alcohol, Smoking, and Substance Involvement Screening Test and its risk assessment to help users understand and interpret the results of student risk. The initial prototype and final version of the dashboard were evaluated by 20 experts, which revealed a significant improvement in the ease of use (P=.047) and usefulness (P=.02) factors and showed a high acceptance mean scores for ease of use (4.2), usefulness (4.46), interface quality (4.29), and sufficiency (4.13).
CONCLUSIONS: The MyAsriGeo geospatial dashboard is useful for monitoring and analyzing drug abuse among school-going youth in Malaysia. It was developed based on the needs of various stakeholders and includes a range of functions. The dashboard was evaluated by a group of experts. Overall, the MyAsriGeo geospatial dashboard is a valuable resource for helping stakeholders understand and respond to the issue of drug abuse among youth.