A
Arafatur Rahman
Researcher at Universiti Malaysia Pahang
Publications - 54
Citations - 950
Arafatur Rahman is an academic researcher from Universiti Malaysia Pahang. The author has contributed to research in topics: Computer science & Wireless network. The author has an hindex of 13, co-authored 54 publications receiving 540 citations. Previous affiliations of Arafatur Rahman include International Islamic University Malaysia & IBM.
Papers
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Journal ArticleDOI
PrivacyProtector: Privacy-Protected Patient Data Collection in IoT-Based Healthcare Systems
TL;DR: A practical framework called PrivacyProtector, patient privacy protected data collection, with the objective of preventing these types of attacks, which includes the ideas of secret sharing and share repairing (in case of data loss or compromise) for patients' data privacy.
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Data-driven dynamic clustering framework for mitigating the adverse economic impact of Covid-19 lockdown practices
Arafatur Rahman,Arafatur Rahman,Nafees Zaman,A. Taufiq Asyhari,Fadi Al-Turjman,Md. Zakirul Alam Bhuiyan,Mohamad Fadli Zolkipli +6 more
TL;DR: A data-driven dynamic clustering framework for moderating the adverse economic impact of COVID-19 flare-up is proposed and the idea can be exploited for potentially the next waves of corona virus-related diseases and other upcoming viral life-threatening calamities.
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Scalable machine learning-based intrusion detection system for IoT-enabled smart cities
Arafatur Rahman,A. Taufiq Asyhari,L.S. Leong,Gandeva Bayu Satrya,M. Hai Tao,Mohamad Fadli Zolkipli +5 more
TL;DR: This paper addresses the limitation of centralized IDS for resource-constrained devices by proposing two methods, namely semi-distributed and distributed, that combine well-performing feature extraction and selection and exploit potential fog-edge coordinated analytics.
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TrustData: Trustworthy and Secured Data Collection for Event Detection in Industrial Cyber-Physical System
Hai Tao,Zakirul Alam Bhuiyan,Arafatur Rahman,Tian Wang,Jie Wu,Sinan Q. Salih,Yafeng Li,Thaier Hayajneh +7 more
TL;DR: This article introduces TrustData, a scheme for high-quality data collection for event detection in the ICPS, referred to as “Trust worthy and secured Data collection” scheme, which alleviates authentic data for accumulation at groups of sensor devices in theICPS.
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Economic perspective analysis of protecting big data security and privacy
TL;DR: The objective is to provide economic justification of technical decisions taken to protect the big data and the amount of costs that organizations often spend for it.