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All Journal Data Science Insights
bin Zainuddin, Ahmad Anwar
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Computer Science & IT Engineering

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Journal : Data Science Insights

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Enhancing IoT Security: A Synergy of Machine Learning, Artificial Intelligence, and Blockchain bin Zainuddin, Ahmad Anwar; Sairin, Haziqah; Mazlan, Izzah Atirah; Muslim, Nur Najma Aisyah; Wan Sabarudin, Wan Afiqah Syahmina
Data Science Insights Vol. 2 No. 1 (2024): Journal of Data Science Insights
Publisher : PT Visi Media Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63017/jdsi.v2i1.11

Abstract

With the advancement of technological age, the growth of technology not only affecting the network and security but also the Internet of Things (IoT), this invites the need for robust cybersecurity solutions become increasingly important. To further enhance the existing safety mechanisms used in the IoT industry, the assimilation of Machine Learning (ML) with Artificial Intelligence (AI) along with the technology of blockchain can further offers a high potential solution in order to face the challenges faced in the IoT security. ML and AI algorithms can enhance the detection and prevention by reviewing variety of data, recognizing patterns and predicting the potential vulnerabilities of the cyber threats in IoT. Blockchain, on the other hand, provides a decentralized and tamper-proof platform for secure data storage and transactions. By leveraging these technologies, IoT systems can achieve a sustainable security, ensuring the protection of sensitive and important information as well as protecting the Confidentiality, Availability, and Integrity (CIA) triad of the infrastructure of the network. This research incorporates the variety of machine learning approaches, including the trees of decision, the K-nearest neighbours, the artificial neural networks, convolutional neural networks, the support of vector machines, Bayesian networks, ensemble classifiers, genetic programming, logistic regression as well as the deep learning tactics. Through this, the deriving insights of raw data can then help these technologies to aim and create a modern and dynamically improved security solutions for the evolving landscape of IoT devices. Future research should focus these upcoming issues in order to fully comprehend potential of ML applications in security intelligence of IoT.  
Revolutionizing Healthcare: A Comprehensive Review of Metaverse Integration for Enhanced Patient Outcomes, Medical Practices, The Potential Applications, Challenges and Future Direction bin Zainuddin, Ahmad Anwar; Md Saifuddin , Muhammad Hafiz Faruqi; Wan Azman , Wan Muhammad Arif; Fuadi , Abdul Ghafur; Ahmad Nadzri , Ahmad Adam Nadzeeran; Mohamad Fadil , Muhammad Hussaini; Aisyah Ruzaidi, Nuramiratul
Data Science Insights Vol. 2 No. 1 (2024): Journal of Data Science Insights
Publisher : PT Visi Media Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63017/jdsi.v2i1.12

Abstract

Integrating the Metaverse into the healthcare system can significantly improve patient outcomes, medical education, and healthcare practices. This study examines the various uses of the Metaverse, emphasizing the essential technologies that make it possible, such as Augmented Reality (AR), Virtual Reality (VR), Extended Reality (XR), and digital twins for personalized care. The report highlights the challenges that healthcare professionals may face while suggesting future paths in the healthcare field. Topics examined include telemedicine, medical education, and the potential advancements that can be achieved with AR, VR, XR, and digital twins. Notable uses encompass virtual counseling, medical training and education, digital therapeutics, and telemedicine. While integrating the Metaverse into healthcare can significantly enhance patient care, it may pose privacy and security risks, incur high costs, require legal compliance, and affect trust in patient-technology relationships. However, future trends should address security and legal issues, balance social and virtual life, and enhance medical training and education. By using augmented reality (AR), virtual reality (VR), extended reality (XR), and digital twins, the healthcare industry can improve patient communication, research and decision-making processes, remote healthcare services, precise medical education training, and tailored patient care. These technologies present a unique opportunity to transform healthcare while addressing privacy, security, and sustainability issues. The purpose of this paper is to review the topic comprehensively, provide suggestions for future research and advancement in this domain, and provide insights into the potential of the Metaverse to revolutionize healthcare.
Integrating IoT and Blockchain for Enhanced Security: Challenges and Solutions bin Zainuddin, Ahmad Anwar; binti Mortadza, Aina Syazana; binti Musa , Faheyra Ezzah
Data Science Insights Vol. 2 No. 1 (2024): Journal of Data Science Insights
Publisher : PT Visi Media Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63017/jdsi.v2i1.17

Abstract

The integration of Internet of Things (IoT) and blockchain integration addresses security concerns in IoT devices through decentralized networks. Challenges include scalability, interoperability, and privacy. Proposed solutions involve decision frameworks, lightweight consensus mechanisms, and hybrid architectures. Smart contracts and privacy-preserving techniques enhance secure transactions. Integration benefits industries like healthcare, supply chain, and energy by improving efficiency and transparency. The methodology involves selecting a blockchain platform, designing a consensus mechanism, developing smart contracts, and integrating IoT devices. Challenges like data ownership and governance can be mitigated through policies and privacy-preserving techniques, ultimately optimizing operations, and improving customer satisfaction across industries.
Co-Authors Ahmad Nadzri , Ahmad Adam Nadzeeran Aisyah Ruzaidi, Nuramiratul binti Mortadza, Aina Syazana binti Musa , Faheyra Ezzah Fuadi , Abdul Ghafur Mazlan, Izzah Atirah Md Saifuddin , Muhammad Hafiz Faruqi Mohamad Fadil , Muhammad Hussaini Muslim, Nur Najma Aisyah Sairin, Haziqah Wan Azman , Wan Muhammad Arif Wan Sabarudin, Wan Afiqah Syahmina