Effectively detecting operational anomalies in large-scale IoT data infrastructures by using a GAN-based predictive model
Quality of data services is crucial for operational large-scale internet-of-things (IoT) research
data infrastructure, in particular when serving large amounts of distributed users. Effectively …
data infrastructure, in particular when serving large amounts of distributed users. Effectively …
MAP based modeling method and performance study of a task offloading scheme with time-correlated traffic and VM repair in MEC systems
Y Wang, X Han, S Jin - Wireless Networks, 2023 - Springer
Abstract Mobile Edge Computing (MEC) has evolved into a key technology that can
leverage resources of computing, storage and network deployed at the proximity of the …
leverage resources of computing, storage and network deployed at the proximity of the …
Industry-and academic-based trends in pavement roughness inspection technologies over the past five decades: A critical review
Roughness is widely used as a primary measure of pavement condition. It is also the key
indicator of the riding quality and serviceability of roads. The high demand for roughness …
indicator of the riding quality and serviceability of roads. The high demand for roughness …
A federated learning and blockchain framework for physiological signal classification based on continual learning
A key challenge of physiological signal processing in the Internet of Medical Things is that
physiological signals usually have dynamic distribution changes. Another challenge is that …
physiological signals usually have dynamic distribution changes. Another challenge is that …
Excavating multimodal correlation for representation learning
A majority of previous methods for multimodal representation learning ignore the rich
correlation information inherently stored in each sample, leading to a lack of robustness …
correlation information inherently stored in each sample, leading to a lack of robustness …
DANTD: A deep abnormal network traffic detection model for security of industrial internet of things using high-order features
G Shi, X Shen, F Xiao, Y He - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
With the development of blockchain, artificial intelligence, and data mining technology,
abnormal network traffic data has become easy to obtain. The traffic detection model detects …
abnormal network traffic data has become easy to obtain. The traffic detection model detects …
Tbdb: Token bucket-based dynamic batching for resource scheduling supporting neural network inference in intelligent consumer electronics
Consumer electronics such as mobile phones, wearable devices, and vehicle electronics
use many intelligent applications such as voice commands, machine translation, and face …
use many intelligent applications such as voice commands, machine translation, and face …
Secure Firmware Update: Challenges and Solutions
L Catuogno, C Galdi - Cryptography, 2023 - mdpi.com
The pervasiveness of IoT and embedded devices allows the deployment of services that
were unthinkable only few years ago. Such devices are typically small, run unattended …
were unthinkable only few years ago. Such devices are typically small, run unattended …
MEMBER: A multi-task learning model with hybrid deep features for network intrusion detection
With the continuous occurrence of cybersecurity incidents, network intrusion detection has
become one of the most critical issues in cyber ecosystems. Although previous machine …
become one of the most critical issues in cyber ecosystems. Although previous machine …
Anomaly detection of train wheels utilizing short-time Fourier transform and unsupervised learning algorithms
Anomaly detection of train wheels helps railway operators to find wheel defects and save
cost by enabling condition-based maintenance. Existing approaches focus on applications …
cost by enabling condition-based maintenance. Existing approaches focus on applications …