An Asynchronous Federated Learning Arbitration Model for Low-Rate DDoS Attack Detection
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3247512
Abstract: Low-rate Distributed Denial of Service (LDDoS) attacks have been one of the most notorious network security threats, which use periodic slight multi-variate time series pulse flows to degrade network quality. Limited by the poor data… read more here.
Keywords: learning arbitration; federated learning; low rate; attack detection ... See more keywords
A Triple-Step Asynchronous Federated Learning Mechanism for Client Activation, Interaction Optimization, and Aggregation Enhancement
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3188556
Abstract: Federated Learning in asynchronous mode (AFL) is attracting much attention from both industry and academia to build intelligent cores for various Internet of Things (IoT) systems and services by harnessing sensitive data and idle computing… read more here.
Keywords: interaction; client; federated learning; triple step ... See more keywords
Efficient Asynchronous Federated Learning Research in the Internet of Vehicles
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3230412
Abstract: Federated learning (FL) is a distributed machine learning paradigm that ensures data do not leave local devices. Data sharing problems can be addressed by FL in untrusted environments, e.g., the Internet of Vehicles (IoV). However,… read more here.
Keywords: efficient asynchronous; federated learning; reduce communication; internet vehicles ... See more keywords
Scheduling and Securing Asynchronous Federated Learning Through Cooperative Jamming
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Cognitive Communications and Networking"
DOI: 10.1109/tccn.2025.3623377
Abstract: Asynchronous federated learning (AFL) tackles the straggler effect of traditional synchronous federated learning (SFL). Yet, AFL may face limited (communication, computation, and energy) resources and security threats, especially in wireless settings. This paper presents a… read more here.
Keywords: asynchronous federated; scheduling securing; model; federated learning ... See more keywords
MODA: Model Ownership Deprivation Attack in Asynchronous Federated Learning
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Dependable and Secure Computing"
DOI: 10.1109/tdsc.2023.3348204
Abstract: Training a deep learning model from scratch requires a great deal of available labeled data, computation resources, and expert knowledge. Thus, the time-consuming and complicated learning procedure catapulted the trained model to valuable intellectual property… read more here.
Keywords: model ownership; asynchronous federated; model; federated learning ... See more keywords
Staleness-Controlled Asynchronous Federated Learning: Accuracy and Efficiency Tradeoff
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Mobile Computing"
DOI: 10.1109/tmc.2024.3416216
Abstract: Federated Learning (FL) is an emerging distributed learning paradigm with the privacy-preserving advantage of collaboratively training a shared model across multiple participants. Considering the prevailing device heterogeneity circumstance in practice, asynchronous interaction is introduced into… read more here.
Keywords: asynchronous federated; staleness controlled; controlled asynchronous; accuracy ... See more keywords
Anti-Byzantine attacks enabled vehicle selection for asynchronous federated learning in vehicular edge computing
Sign Up to like & getrecommendations! Published in 2024 at "China Communications"
DOI: 10.23919/jcc.fa.2023-0718.202408
Abstract: In vehicle edge computing (VEC), asynchronous federated learning (AFL) is used, where the edge receives a local model and updates the global model, effectively reducing the global aggregation latency. Due to different amounts of local… read more here.
Keywords: vehicle; edge computing; asynchronous federated; byzantine attacks ... See more keywords
Improved Asynchronous Federated Learning for Data Injection Pollution
Sign Up to like & getrecommendations! Published in 2025 at "Algorithms"
DOI: 10.3390/a18060313
Abstract: In view of the problems of data pollution, incomplete feature extraction, and poor multi-network parameter sharing and transmission under the federated learning framework of deep learning, this article proposes an improved asynchronous federated learning algorithm… read more here.
Keywords: improved asynchronous; asynchronous federated; data injection; federated learning ... See more keywords
Large Language Model and Digital Twins Empowered Asynchronous Federated Learning for Secure Data Sharing in Intelligent Labeling
Sign Up to like & getrecommendations! Published in 2024 at "Mathematics"
DOI: 10.3390/math12223550
Abstract: With the advancement of the large language model (LLM), the demand for data labeling services has increased dramatically. Big models are inseparable from high-quality, specialized scene data, from training to deploying application iterations to landing… read more here.
Keywords: intelligent labeling; asynchronous federated; language; model ... See more keywords
Improved Federated Learning Incentive Mechanism Algorithm Based on Explainable DAG Similarity Evaluation
Sign Up to like & getrecommendations! Published in 2025 at "Mathematics"
DOI: 10.3390/math13213507
Abstract: In vehicular networks, inter-vehicle data sharing and collaborative computing improve traffic efficiency and driving experience. However, centralized processing faces challenges with privacy, communication bottlenecks, and real-time performance. This paper proposes a trust assessment mechanism for… read more here.
Keywords: improved federated; asynchronous federated; mechanism; federated learning ... See more keywords