Intrusion detection in internet of things systems: a review on design approaches leveraging multi-access edge computing, machine learning, and datasets
The explosive growth of the Internet of Things (IoT) applications has imposed a dramatic
increase of network data and placed a high computation complexity across various …
increase of network data and placed a high computation complexity across various …
[HTML][HTML] Quantifying the need for supervised machine learning in conducting live forensic analysis of emergent configurations (ECO) in IoT environments
Abstract Machine learning has been shown as a promising approach to mine larger
datasets, such as those that comprise data from a broad range of Internet of Things devices …
datasets, such as those that comprise data from a broad range of Internet of Things devices …
A many-objective optimization based federal deep generation model for enhancing data processing capability in IoT
X Cai, Y Lan, Z Zhang, J Wen, Z Cui… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The rapid progress of artificial intelligence expands its wide applicability in Internet of Things
(IoT). Meanwhile, data insufficient and data source privacy are key supply chain challenges …
(IoT). Meanwhile, data insufficient and data source privacy are key supply chain challenges …
A goal-driven approach for deploying self-adaptive IoT systems
Engineering Internet of Things (IoT) systems is a challenging task partly due to the
dynamicity and uncertainty of the environment including the involvement of the human in the …
dynamicity and uncertainty of the environment including the involvement of the human in the …
Self-commissioning industrial IoT-systems in process automation: a reference architecture
H Koziolek, A Burger… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
Distributed control systems are currently evolving towards Industrial Internet-of-Things (IIoT)
systems. However, they still suffer from complex commissioning processes that incur high …
systems. However, they still suffer from complex commissioning processes that incur high …
A machine learning-driven approach for proactive decision making in adaptive architectures
H Muccini, K Vaidhyanathan - 2019 IEEE international …, 2019 - ieeexplore.ieee.org
Self-adaptation is nowadays considered to be the best solution to dynamically reconfigure a
system in the occurrence of deviations from the expected quality of service (QoS) …
system in the occurrence of deviations from the expected quality of service (QoS) …
Artifical Intelligence Librarian as Promotion of IAIN Lhokseumawe Library in the Revolutionary Era 4.0
Abstract Era 4.0. is a revolution in the industrial world, in the era referred to as the
phenomenon distruptive innovation. In the industrial era 4.0, the emphasis lies on the digital …
phenomenon distruptive innovation. In the industrial era 4.0, the emphasis lies on the digital …
FloBP: a model-driven approach for developing and executing IoT-enhanced business processes
The capability to integrate Internet of Things (IoT) technologies into business processes
(BPs) has emerged as a transformative paradigm, offering unprecedented opportunities for …
(BPs) has emerged as a transformative paradigm, offering unprecedented opportunities for …
OpenPnP: a plug-and-produce architecture for the industrial internet of things
Industrial control systems are complex, software-intensive systems that manage mission-
critical production processes. Commissioning such systems requires installing, configuring …
critical production processes. Commissioning such systems requires installing, configuring …
MSL: A pattern language for engineering self-adaptive systems
In architecture-based self-adaptation of decentralized systems, design patterns have been
introduced to ease the design of complex adaptation solutions that usually require the …
introduced to ease the design of complex adaptation solutions that usually require the …