Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if
harnessed appropriately, may deliver the best of expectations over many application sectors …
harnessed appropriately, may deliver the best of expectations over many application sectors …
Educational data mining and learning analytics: An updated survey
This survey is an updated and improved version of the previous one published in 2013 in
this journal with the title “data mining in education”. It reviews in a comprehensible and very …
this journal with the title “data mining in education”. It reviews in a comprehensible and very …
A survey on machine learning for data fusion
Data fusion is a prevalent way to deal with imperfect raw data for capturing reliable, valuable
and accurate information. Comparing with a range of classical probabilistic data fusion …
and accurate information. Comparing with a range of classical probabilistic data fusion …
Machine learning in IoT security: Current solutions and future challenges
The future Internet of Things (IoT) will have a deep economical, commercial and social
impact on our lives. The participating nodes in IoT networks are usually resource …
impact on our lives. The participating nodes in IoT networks are usually resource …
An overview of IoT sensor data processing, fusion, and analysis techniques
In the recent era of the Internet of Things, the dominant role of sensors and the Internet
provides a solution to a wide variety of real-life problems. Such applications include smart …
provides a solution to a wide variety of real-life problems. Such applications include smart …
[HTML][HTML] Evaluating Federated Learning for intrusion detection in Internet of Things: Review and challenges
Abstract The application of Machine Learning (ML) techniques to the well-known intrusion
detection systems (IDS) is key to cope with increasingly sophisticated cybersecurity attacks …
detection systems (IDS) is key to cope with increasingly sophisticated cybersecurity attacks …
Smart anomaly detection in sensor systems: A multi-perspective review
Anomaly detection is concerned with identifying data patterns that deviate remarkably from
the expected behavior. This is an important research problem, due to its broad set of …
the expected behavior. This is an important research problem, due to its broad set of …
Graph neural networks for anomaly detection in industrial internet of things
The Industrial Internet of Things (IIoT) plays an important role in digital transformation of
traditional industries toward Industry 4.0. By connecting sensors, instruments, and other …
traditional industries toward Industry 4.0. By connecting sensors, instruments, and other …
Secure healthcare data aggregation and transmission in IoT—A survey
Internet of medical things (IoMT) is getting researchers' attention due to its wide applicability
in healthcare. Smart healthcare sensors and IoT enabled medical devices exchange data …
in healthcare. Smart healthcare sensors and IoT enabled medical devices exchange data …
Machine learning for resource management in cellular and IoT networks: Potentials, current solutions, and open challenges
Internet-of-Things (IoT) refers to a massively heterogeneous network formed through smart
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …