A comprehensive survey on machine learning-based big data analytics for IoT-enabled smart healthcare system

W Li, Y Chai, F Khan, SRU Jan, S Verma… - Mobile networks and …, 2021 - Springer
The outbreak of chronic diseases such as COVID-19 has made a renewed call for providing
urgent healthcare facilities to the citizens across the globe. The recent pandemic exposes …

Cybersecurity of industrial cyber-physical systems: A review

H Kayan, M Nunes, O Rana, P Burnap… - ACM Computing Surveys …, 2022 - dl.acm.org
Industrial cyber-physical systems (ICPSs) manage critical infrastructures by controlling the
processes based on the “physics” data gathered by edge sensor networks. Recent …

[HTML][HTML] Evolving techniques in cyber threat hunting: A systematic review

A Mahboubi, K Luong, H Aboutorab, HT Bui… - Journal of Network and …, 2024 - Elsevier
In the rapidly changing cybersecurity landscape, threat hunting has become a critical
proactive defense against sophisticated cyber threats. While traditional security measures …

A blockchain-based decentralized, fair and authenticated information sharing scheme in zero trust internet-of-things

Y Liu, X Hao, W Ren, R **ong, T Zhu… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Internet-of-Things (IoT) are increasingly operating in the zero-trust environments where any
devices and systems may be compromised and hence untrusted. In addition, data collected …

Cloud‐based fault prediction using IoT in office automation for improvisation of health of employees

M Uppal, D Gupta, S Juneja, G Dhiman… - Journal of Healthcare …, 2021 - Wiley Online Library
The novel paradigm of Internet of Things (IoT) is gaining recognition in the numerous
scenarios promoting the pervasive presence of smart things around us through its …

Real-time data visual monitoring of triboelectric nanogenerators enabled by Deep learning

H Zhang, T Liu, X Zou, Y Zhu, M Chi, D Wu, K Jiang… - Nano Energy, 2024 - Elsevier
The rapid advancement of smart sensors and logic algorithms has propelled the widespread
adoption of the Internet of Things (IoT) and expedited the advent of the intelligent era. The …

FedAdapt: Adaptive Offloading for IoT Devices in Federated Learning

D Wu, R Ullah, P Harvey, P Kilpatrick… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
Applying federated learning (FL) on Internet of Things (IoT) devices is necessitated by the
large volumes of data they produce and growing concerns of data privacy. However, there …

A review of on-device machine learning for IoT: An energy perspective

N Tekin, A Aris, A Acar, S Uluagac, VC Gungor - Ad Hoc Networks, 2024 - Elsevier
Recently, there has been a substantial interest in on-device Machine Learning (ML) models
to provide intelligence for the Internet of Things (IoT) applications such as image …

A survey on deep learning for challenged networks: Applications and trends

K Bochie, MS Gilbert, L Gantert, MSM Barbosa… - Journal of Network and …, 2021 - Elsevier
Computer networks are dealing with growing complexity, given the ever-increasing volume
of data produced by all sorts of network nodes. Performance improvements are a non-stop …

Using machine learning for dynamic authentication in telehealth: A tutorial

M Hazratifard, F Gebali, M Mamun - Sensors, 2022 - mdpi.com
Telehealth systems have evolved into more prevalent services that can serve people in
remote locations and at their homes via smart devices and 5G systems. Protecting the …