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- 저자 : Yusoff Mohd Najwadi (검색결과 4 건)
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IoT Adoption by the Young Consumer: An Extended ASE Perspective
Arif Mahmud,Mohd Najwadi Yusoff,Mohd Heikal Husin 한국경영정보학회 2022 Asia Pacific Journal of Information Systems Vol.32 No.4
Home theft and burglary are prevalent in Dhaka city. Internet of things (IoT), in contrast, is commonly recognized as among the most advanced home security systems. However, the factors that attract young people to use IoT for household security have yet to be examined. Consequently, the purpose of this article is to validate the attitude-social influence-self-efficacy (ASE) model with personal innovativeness and perceived trust. We collected data from Dhaka citizens aged 15 to 24 using a purposive sample technique and 370 valid responses were chosen for the study. According to the analysis, all of our proposed hypotheses were found significant with a 73.6% variance. Furthermore, the effects of attitude and social influence were shown to be the highest and lowest, respectively, and trust and innovativeness were both nearly strong main predictors of ASE. Significantly, since this is one of the few studies in the technology adoption domain using this model, a solid foundation for IoT adoption for security purposes is established.
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Mahmud, Arif,Husin, Mohd Heikal,Yusoff, Mohd Najwadi Korea Institute of Science and Technology Informat 2022 Journal of Information Science Theory and Practice Vol.10 No.2
The research in the literature review on Internet of Things (IoT) adoption from an individual consumer viewpoint is minimal and has not yet been fully investigated. Therefore, the objectives of this study are to analyze the growth of IoT in recent years and to conduct a weight analysis of the factors that affect acceptance intentions and real usage of IoT-enabled services. For the review, we analyzed 87 publications from 13 conferences and 54 journals published during the period 2014-2020 about consumer adoption of IoT. Following the study, we discovered an unprecedented increase in the number of articles published in the last seven years, which points to an emerging area with an enormous prospect. Furthermore, the weight analysis outcome was associated with the diagrammatic representation in this study. After that, this research developed a generalized consumer IoT adoption model based on the 12 best predictors derived from frequency count and weight analysis, which had the highest predictive power for calculating IoT adoption. This paper further acknowledges the study's theoretical and practical contributions, as well as its shortcomings, and proposes further research directions for future researchers.
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Abdullahi Aminu Kazaure,Aman Jantan,Mohd Najwadi Yusoff Korea Institute of Science and Technology Informat 2024 Journal of Information Science Theory and Practice Vol.12 No.1
An online social network is a platform that is continuously expanding, which enables groups of people to share their views and communicate with one another using the Internet. The social relations among members of the public are significantly improved because of this gesture. Despite these advantages and opportunities, criminals are continuing to broaden their attempts to exploit people by making use of techniques and approaches designed to undermine and exploit their victims for criminal activities. The field of digital forensics, on the other hand, has made significant progress in reducing the impact of this risk. Even though most of these digital forensic investigation techniques are carried out manually, most of these methods are not usually appropriate for use with online social networks due to their complexity, growth in data volumes, and technical issues that are present in these environments. In both civil and criminal cases, including sexual harassment, intellectual property theft, cyberstalking, online terrorism, and cyberbullying, forensic investigations on social media platforms have become more crucial. This study explores the use of machine learning techniques for addressing criminal incidents on social media platforms, particularly during forensic investigations. In addition, it outlines some of the difficulties encountered by forensic investigators while investigating crimes on social networking sites.
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Digital Forensics Investigation Approaches in Mitigating Cybercrimes: A Review
Kazaure Abdullahi Aminu,Jantan Aman,Yusoff Mohd Najwadi 한국과학기술정보연구원 2023 Journal of Information Science Theory and Practice Vol.11 No.4
Cybercrime is a significant threat to Internet users, involving crimes committed using computers or computer networks. The landscape of cyberspace presents a complex terrain, making the task of tracing the origins of sensitive data a formidable and often elusive endeavor. However, tracing the source of sensitive data in online cyberspace is critically challenging, and detecting cyber-criminals on the other hand remains a time-consuming process, especially in social networks. Cyber-criminals target individuals for financial gain or to cause harm to their assets, resulting in the loss or theft of millions of user data over the past few decades. Forensic professionals play a vital role in conducting successful investigations and acquiring legally acceptable evidence admissible in court proceedings using modern techniques. This study aims to provide an overview of forensic investigation methods for extracting digital evidence from computer systems and mobile devices to combat persistent cybercrime. It also discusses current cybercrime issues and mitigation procedures.
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