Variational few-shot learning for microservice-oriented intrusion detection in distributed industrial IoT
Along with the popularity of the Internet of Things (IoT) techniques with several
computational paradigms, such as cloud and edge computing, microservice has been …
computational paradigms, such as cloud and edge computing, microservice has been …
Network intrusion detection model based on CNN and GRU
B Cao, C Li, Y Song, Y Qin, C Chen - Applied Sciences, 2022 - mdpi.com
A network intrusion detection model that fuses a convolutional neural network and a gated
recurrent unit is proposed to address the problems associated with the low accuracy of …
recurrent unit is proposed to address the problems associated with the low accuracy of …
An attention‐based category‐aware GRU model for the next POI recommendation
With the continuous accumulation of users' check‐in data, we can gradually capture users'
behavior patterns and mine users' preferences. Based on this, the next point‐of‐interest …
behavior patterns and mine users' preferences. Based on this, the next point‐of‐interest …
LSTM-autoencoder-based anomaly detection for indoor air quality time-series data
Anomaly detection for indoor air quality (IAQ) data has become an important area of
research as the quality of air is closely related to human health and well-being. However …
research as the quality of air is closely related to human health and well-being. However …
ASTREAM: Data-stream-driven scalable anomaly detection with accuracy guarantee in IIoT environment
Intrusion detection exerts a crucial influence on securing the IIoT driven by anomaly
detection approaches. Dissimilar with the static data, the intrusion detection data is in the …
detection approaches. Dissimilar with the static data, the intrusion detection data is in the …
Deep graph neural network-based spammer detection under the perspective of heterogeneous cyberspace
Due to the severe threat to cyberspace security, detection of online spammers has been a
universal concern of academia. Nowadays, prevailing literature of this field almost leveraged …
universal concern of academia. Nowadays, prevailing literature of this field almost leveraged …
The artificial intelligence technologies in Industry 4.0: A taxonomy, approaches, and future directions
Industry 4.0 transforms the manufacturing sector with dynamic, networked, complex
industrial environments. These environments generate vast amounts of data and require …
industrial environments. These environments generate vast amounts of data and require …
Intelligent approaches toward intrusion detection systems for Industrial Internet of Things: A systematic comprehensive review
M Nuaimi, LC Fourati, BB Hamed - Journal of Network and Computer …, 2023 - Elsevier
Recently years, we have seen the exponential upgrowth of the Industrial Internet of Things
(IIoT), which brings significant benefits to our daily lives, industry, and society. The common …
(IIoT), which brings significant benefits to our daily lives, industry, and society. The common …
Fuzzy detection system for rumors through explainable adaptive learning
Nowadays, rumor spreading has gradually evolved into a kind of organized behaviors,
accompanied with strong uncertainty and fuzziness. However, existing fuzzy detection …
accompanied with strong uncertainty and fuzziness. However, existing fuzzy detection …
Federated intrusion detection in blockchain-based smart transportation systems
M Abdel-Basset, N Moustafa, H Hawash… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
With the integration of the Internet of Things (IoT) in the field of transportation, the Internet of
Vehicles (IoV) turned to be a vital method for designing Smart Transportation Systems (STS) …
Vehicles (IoV) turned to be a vital method for designing Smart Transportation Systems (STS) …