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All Journal International Journal of Advances in Applied Sciences
JosephNg Poh Soon
UCSI University
Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics

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User perceptions of artificial intelligence powered phishing attacks on Facebook's resilient infrastructure JosephNg Poh Soon; Rou Qian Chan; Qian Hui Lee; Dick En Loke; Stevenson Ling Heng Chun; Phan Koo Yuen
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp878-886

Abstract

This study focuses on examining the user perceptions of a cybersecurity certificate transparency (CT) monitoring tool in the context of artificial intelligence (AI) powered phishing attacks on the Facebook platform. Implementing CT monitoring tools is one strategy for preventing these attacks. It reveals a significant level of concern among respondents regarding the potential risks associated with phishing attacks, indicating a growing awareness of the severity of such threats for future resilient infrastructure development. Users' knowledge and understanding of AI-driven phishing threats were found to vary, emphasizing the need for awareness campaigns towards sustainable development education. The study also highlights varying levels of confidence among users in effectively identifying and thwarting phishing efforts, suggesting the importance of user empowerment through improved training, tools, and technologies as responsive institutions. These findings underscore the significance of addressing user concerns, enhancing security awareness, and providing users with the necessary resources to protect themselves against sophisticated phishing attacks. The research contributes to the understanding of user perceptions and lays the groundwork for further improvements in security measures and user education in the fight against phishing threats on Facebook's inclusive growth.
Quantum computing impact of cybersecurity identity verification measures on WhatsApp resilient infrastructure JosephNg Poh Soon; Nair Preeta; Kumar Praveen; Kok Peng Yew; Phan Koo Yuen
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp840-849

Abstract

This study investigates the impact and implications of implementing cybersecurity identity verification on the popular instant messaging platform, WhatsApp. Specifically, it focuses on the effects of such a measure on resilient infrastructure, user perceptions of the platform's branding and trustworthiness, and the cost-effectiveness of this approach in preventing scams, phishing, fraud, and cybercrime. Empirical data collected from a diverse group of WhatsApp users highlight that the introduction of identity verification could potentially enhance transaction efficiency, foster trust, and boost user satisfaction, particularly regarding the platform's security. However, the cost and complexity of implementation pose significant challenges. Despite these hurdles, most users perceive the potential benefits to outweigh the associated costs, pointing to a broad acceptance of such security measures. The study provides practical and theoretical contributions, offering valuable insights for managers and decision-makers at WhatsApp, as well as contributing to academic discussions on digital platform management and security. The research also underscores the societal implications of such a measure, suggesting an increase in trust in digital communication platforms and supporting safer financial transactions on social media. The integration of identity verification on WhatsApp being a responsive institution emerges as a valuable but complex endeavor, demanding careful planning to ensure maximum value creation for all stakeholders.
Co-Authors Dick En Loke Kok Peng Yew Kumar Praveen Nair Preeta Phan Koo Yuen Qian Hui Lee Rou Qian Chan Stevenson Ling Heng Chun