Related references
Note: Only part of the references are listed.
Article
Engineering, Multidisciplinary
Zhe Peng et al.
Summary: This paper proposes VFChain, a verifiable and auditable federated learning framework based on the blockchain system. Verifiability is provided by recording proofs in the blockchain, and auditability is supported by a novel authenticated data structure and secure rotation of the committee. Experimental results demonstrate the effectiveness of VFChain.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Automation & Control Systems
Peng Zhuang et al.
Summary: Blockchain technology, as an immutable distributed ledger, has garnered significant interest in the application of cybersecurity in the smart grid. Despite efforts to utilize blockchain in enhancing smart grid cybersecurity, a comprehensive survey on its application and technological aspects is lacking. This survey aims to provide insights on the latest ideas, architectures, and implementation techniques relevant to blockchain application in smart grid cybersecurity.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Information Systems
Jiale Zhang et al.
Summary: Edge computing is a key technology for intelligent IoT applications, while federated learning is an intelligent edge computing framework. However, recent studies have shown that the federated learning framework is vulnerable to poisoning attacks, where the attacker's local updates can damage the functionality of the global model.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Quoc-Viet Pham et al.
Summary: The research proposes a method for sustainable federated learning using unmanned aerial vehicles for wireless power transfer. By jointly optimizing transmission time, bandwidth allocation, power control, and UAV placement, the goal is to maximize UAV transmit power efficiency.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Yi Liu et al.
Summary: This article proposes a communication-efficient on-device federated learning (FL)-based deep anomaly detection framework for sensing time-series data in IIoT. The framework includes an FL framework, AMCNN-LSTM model, and gradient compression mechanism, which can improve generalization ability, accurately detect anomalies, and enhance communication efficiency.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Hardware & Architecture
Zonghang Li et al.
Summary: Blockchained federated learning, with its security properties such as decentralization, immutability, and traceability, is evolving into a key direction for next-generation AI. BytoChain, a byzantine resistant secure blockchained federated learning framework, improves model verification efficiency and detects byzantine attacks through a PoA consensus. By mitigating various types of attacks, BytoChain demonstrates effectiveness and addresses open issues in security.
Article
Automation & Control Systems
Beibei Li et al.
Summary: The study introduces a novel federated deep learning scheme named DeepFed for detecting cyber threats against industrial CPSs. By designing a new intrusion detection model and federated learning framework, the research successfully achieves secure detection of various cyber threats.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Information Systems
Yang Zhao et al.
Summary: The proposal integrates federated learning and local differential privacy to protect user privacy and reduce communication costs. By introducing three output possibilities to improve accuracy under a small privacy budget, optimal and suboptimal mechanisms are proposed to maximize performance while a hybrid mechanism is formed by combining them, training the model collaboratively. Extensive experiments validate the capability of the proposed algorithms in protecting privacy while ensuring utility.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Ranwa Al Mallah et al.
Summary: This paper examines the new threat posed by using FL in wireless mobile networks, and explores falsified information attacks on the FL process in vehicular networks, demonstrating their impact on model accuracy and convergence time.
2021 IEEE INTELLIGENT VEHICLES SYMPOSIUM WORKSHOPS (IV WORKSHOPS)
(2021)
Article
Computer Science, Artificial Intelligence
Pavlos Papadopoulos et al.
Summary: This paper presents a privacy-preserving decentralized workflow that facilitates trusted federated learning among participants by ensuring data privacy through distributed computation. The proof-of-concept defines a trust framework using decentralized identity technologies under Hyperledger projects Aries/Indy/Ursa.
MACHINE LEARNING AND KNOWLEDGE EXTRACTION
(2021)
Article
Computer Science, Information Systems
Dinh C. Nguyen et al.
Summary: The Internet of Things and artificial intelligence are increasingly intertwined in our daily lives, with Federated Learning emerging as a distributed collaborative AI approach that can play a vital role in intelligent IoT applications. This article provides a comprehensive survey of the emerging applications of FL in IoT networks and highlights its potential in various fields, paving the way for future research directions.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2021)
Article
Engineering, Electrical & Electronic
Tian Li et al.
IEEE SIGNAL PROCESSING MAGAZINE
(2020)
Article
Computer Science, Hardware & Architecture
Chuan Ma et al.
Article
Engineering, Electrical & Electronic
Shiva Raj Pokhrel et al.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2020)
Article
Computer Science, Information Systems
Yi Liu et al.
IEEE INTERNET OF THINGS JOURNAL
(2020)
Article
Computer Science, Artificial Intelligence
Yiqiang Chen et al.
IEEE INTELLIGENT SYSTEMS
(2020)
Article
Computer Science, Hardware & Architecture
Sawsan Abdul Rahman et al.
Article
Computer Science, Information Systems
Zhuo Chen et al.
Article
Computer Science, Information Systems
Wei Yang Bryan Lim et al.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2020)
Article
Computer Science, Theory & Methods
Guowen Xu et al.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2020)
Article
Computer Science, Artificial Intelligence
Qiang Yang et al.
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY
(2019)
Article
Computer Science, Information Systems
Jiawen Kang et al.
IEEE INTERNET OF THINGS JOURNAL
(2019)
Article
Multidisciplinary Sciences
David Silver et al.
