Data fusion approach for collaborative anomaly intrusion detection in blockchain-based systems
Blockchain technology is rapidly changing the transaction behavior and efficiency of
businesses in recent years. Data privacy and system reliability are critical issues that is …
businesses in recent years. Data privacy and system reliability are critical issues that is …
A novel spatial-temporal multi-scale alignment graph neural network security model for vehicles prediction
Traffic flow forecasting is indispensable in today's society and regarded as a key problem for
Intelligent Transportation Systems (ITS), as emergency delays in vehicles can cause serious …
Intelligent Transportation Systems (ITS), as emergency delays in vehicles can cause serious …
Qos prediction and adversarial attack protection for distributed services under dlaas
W Liang, Y Li, J Xu, Z Qin, D Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deep-Learning-as-a-service (DLaaS) has received increasing attention due to its novelty as
a diagram for deploying deep learning techniques. However, DLaaS faces performance and …
a diagram for deploying deep learning techniques. However, DLaaS faces performance and …
Effective scaling of blockchain beyond consensus innovations and moore's law: Challenges and opportunities
As an emerging technology, blockchain has achieved great success in numerous
application scenarios, from intelligent healthcare to smart cities. However, a long-standing …
application scenarios, from intelligent healthcare to smart cities. However, a long-standing …
A deep reinforcement learning-based resource management game in vehicular edge computing
X Zhu, Y Luo, A Liu, NN **ong… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) is a promising paradigm that leverages the vehicles to
offload computation tasks to the nearby VEC server with the aim of supporting the low …
offload computation tasks to the nearby VEC server with the aim of supporting the low …
Multi-range bidirectional mask graph convolution based GRU networks for traffic prediction
Traffic prediction is a critical component in intelligent traffic systems, as the complicated
spatial relationships and temporal dynamics in the traffic data make it a challenging task …
spatial relationships and temporal dynamics in the traffic data make it a challenging task …
Deep neural network security collaborative filtering scheme for service recommendation in intelligent cyber–physical systems
Cyber–physical systems (CPSs) is a security real-time embedded system. CPS integrates
the information sensed by the current physical sensors, through high-speed real-time …
the information sensed by the current physical sensors, through high-speed real-time …
Backdoor attack on machine learning based android malware detectors
Machine learning (ML) has been widely used for malware detection on different operating
systems, including Android. To keep up with malware's evolution, the detection models …
systems, including Android. To keep up with malware's evolution, the detection models …
Fast sparse flow field prediction around airfoils via multi-head perceptron based deep learning architecture
In order to obtain the information about flow field, traditional computational fluid dynamics
methods need to solve the Navier-Stokes equations on the mesh with boundary conditions …
methods need to solve the Navier-Stokes equations on the mesh with boundary conditions …
Secure fusion approach for the internet of things in smart autonomous multi-robot systems
The application of smart autonomous multi-robot systems has received increasing attention
and dramatically developed, and this situation greatly promotes the development of the …
and dramatically developed, and this situation greatly promotes the development of the …