Hierarchical adversarial attacks against graph-neural-network-based IoT network intrusion detection system
The advancement of Internet of Things (IoT) technologies leads to a wide penetration and
large-scale deployment of IoT systems across an entire city or even country. While IoT …
large-scale deployment of IoT systems across an entire city or even country. While IoT …
Edge-enabled two-stage scheduling based on deep reinforcement learning for internet of everything
Nowadays, the concept of Internet of Everything (IoE) is becoming a hotly discussed topic,
which is playing an increasingly indispensable role in modern intelligent applications. These …
which is playing an increasingly indispensable role in modern intelligent applications. These …
Toward trustworthy ai: Blockchain-based architecture design for accountability and fairness of federated learning systems
Federated learning is an emerging privacy-preserving AI technique where clients (ie,
organizations or devices) train models locally and formulate a global model based on the …
organizations or devices) train models locally and formulate a global model based on the …
Reputation-aware supplier assessment for blockchain-enabled supply chain in industry 4.0
X Xu, J Gu, H Yan, W Liu, L Qi… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In Industry 4.0, the development of intelligent supply chains is the key to improving
enterprise efficiency and customer satisfaction. At present, the strategy with blockchain to …
enterprise efficiency and customer satisfaction. At present, the strategy with blockchain to …
Deep reinforcement learning-based energy-efficient edge computing for internet of vehicles
Mobile network operators (MNOs) allocate computing and caching resources for mobile
users by deploying a central control system. Existing studies mainly use programming and …
users by deploying a central control system. Existing studies mainly use programming and …
Highly accurate energy consumption forecasting model based on parallel LSTM neural networks
The main challenges of the energy consumption forecasting problem are the concerns for
reliability, stability, efficiency and accuracy of the forecasting methods. The existing …
reliability, stability, efficiency and accuracy of the forecasting methods. The existing …
Uav-assisted task offloading for iot in smart buildings and environment via deep reinforcement learning
J Xu, D Li, W Gu, Y Chen - Building and Environment, 2022 - Elsevier
With the rapid development of Internet of Things (IoT) techniques, IoT devices with sensors
have been widely deployed and used in smart buildings and environment, and the …
have been widely deployed and used in smart buildings and environment, and the …
Time-aware missing healthcare data prediction based on ARIMA model
L Kong, G Li, W Rafique, S Shen, Q He… - … ACM transactions on …, 2022 - ieeexplore.ieee.org
Healthcare uses state-of-the-art technologies (such as wearable devices, blood glucose
meters, electrocardiographs), which results in the generation of large amounts of data …
meters, electrocardiographs), which results in the generation of large amounts of data …
A knowledge-driven anomaly detection framework for social production system
In the social production system, image data are rapidly generated from almost all fields such
as factories, hospitals, and transportation, promoting higher requirements for image anomaly …
as factories, hospitals, and transportation, promoting higher requirements for image anomaly …
[HTML][HTML] A blockchain and IoT-based lightweight framework for enabling information transparency in supply chain finance
Abstract Supply Chain Finance (SCF) refers to the financial service in which banks rely on
core enterprises to manage the capital flow and logistics of upstream and downstream …
core enterprises to manage the capital flow and logistics of upstream and downstream …