Trustworthy federated learning: A survey
Federated Learning (FL) has emerged as a significant advancement in the field of Artificial
Intelligence (AI), enabling collaborative model training across distributed devices while …
Intelligence (AI), enabling collaborative model training across distributed devices while …
Adaptive resource allocation for blockchain-based federated learning in Internet of Things
The fast development of mobile communication and artificial intelligence (AI) technologies
greatly promotes the prosperity of the Internet of Things (IoT), where various types of IoT …
greatly promotes the prosperity of the Internet of Things (IoT), where various types of IoT …
Federated unlearning with momentum degradation
Data privacy is becoming increasingly important as data becomes more valuable, as
evidenced by the enactment of right-to-be-forgotten laws and regulations. However, in a …
evidenced by the enactment of right-to-be-forgotten laws and regulations. However, in a …
Balancing privacy protection and interpretability in federated learning
Federated learning (FL) aims to collaboratively train the global model in a distributed
manner by sharing the model parameters from local clients to a central server, thereby …
manner by sharing the model parameters from local clients to a central server, thereby …
Reinvigorating sustainability in Internet of Things marketing: Framework for multi-round real-time bidding with game machine learning
R Zhang, C Jiang, J Zhang, J Fan, J Ren, H Xia - Internet of Things, 2023 - Elsevier
Auction-based incentive mechanisms can satisfy the heterogeneous demands of both
Demand Side Platforms (DSP) and Supply Side Platforms (SSP) in Internet of Things (IoT) …
Demand Side Platforms (DSP) and Supply Side Platforms (SSP) in Internet of Things (IoT) …
Server-initiated federated unlearning to eliminate impacts of low-quality data
Federated unlearning (FUL) is an emerging distributed machine learning paradigm which
enables the removal or unlearning of specific training data effects from trained Federated …
enables the removal or unlearning of specific training data effects from trained Federated …
A visually secure image encryption method based on semi-tensor product compressed sensing and IWT-HD-SVD embedding
Z Shuo, H Pijun, C Yongguang, B Wang - Heliyon, 2023 - cell.com
The conventional approach for images encryption entails transforming a regular image into
an encrypted image that resembles noise. However, this noise-like encrypted image is …
an encrypted image that resembles noise. However, this noise-like encrypted image is …
Hierarchical quantum information splitting of an arbitrary two-qubit state based on a decision tree
D Li, Y Zheng, X Liu, J Zhou, Y Tan, X Yang, M Liu - Mathematics, 2022 - mdpi.com
Quantum informatics is a new subject formed by the intersection of quantum mechanics and
informatics. Quantum communication is a new way to transmit quantum states through …
informatics. Quantum communication is a new way to transmit quantum states through …
A Novel Resource Management Framework for Blockchain-Based Federated Learning in IoT Networks
At present, the centralized learning models, used for IoT applications generating large
amount of data, face several challenges such as bandwidth scarcity, more energy …
amount of data, face several challenges such as bandwidth scarcity, more energy …
Symbiotic Blockchain Consensus: Cognitive Backscatter Communications-enabled Wireless Blockchain Consensus
The wireless blockchain network (WBN) concept, born from the blockchain deployed in
wireless networks, has appealed to many network scenarios. Blockchain consensus …
wireless networks, has appealed to many network scenarios. Blockchain consensus …