Securing federated learning with blockchain: a systematic literature review

被引:54
作者
Qammar, Attia [1 ]
Karim, Ahmad [2 ]
Ning, Huansheng [1 ]
Ding, Jianguo [3 ]
机构
[1] Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing, Peoples R China
[2] Bahauddin Zakariya Univ, Dept Informat Technol, Multan, Pakistan
[3] Blekinge Inst Technol, Dept Comp Sci, Karlskrona, Sweden
关键词
Federated learning; Blockchain; Security; Privacy; Blockchain-based FL; Systematic literature review; TECHNOLOGY; CHALLENGES; FRAMEWORK; MECHANISM;
D O I
10.1007/s10462-022-10271-9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Federated learning (FL) is a promising framework for distributed machine learning that trains models without sharing local data while protecting privacy. FL exploits the concept of collaborative learning and builds privacy-preserving models. Nevertheless, the integral features of FL are fraught with problems, such as the disclosure of private information, the unreliability of uploading model parameters to the server, the communication cost, etc. Blockchain, as a decentralized technology, is able to improve the performance of FL without requiring a centralized server and also solves the above problems. In this paper, a systematic literature review on the integration of Blockchain in federated learning was considered with the analysis of the existing FL problems that can be compensated. Through carefully screening, most relevant studies are included and research questions cover the potential security and privacy attacks in traditional federated learning that can be solved by blockchain as well as the characteristics of Blockchain-based FL. In addition, the latest Blockchain-based approaches to federated learning have been studied in-depth in terms of security and privacy, records and rewards, and verification and accountability. Furthermore, open issues related to the combination of Blockchain and FL are discussed. Finally, future research directions for the robust development of Blockchain-based FL systems are proposed.
引用
收藏
页码:3951 / 3985
页数:35
相关论文
共 91 条
[1]   A Survey on Federated Learning: The Journey From Centralized to Distributed On-Site Learning and Beyond [J].
AbdulRahman, Sawsan ;
Tout, Hanine ;
Ould-Slimane, Hakima ;
Mourad, Azzam ;
Talhi, Chamseddine ;
Guizani, Mohsen .
IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (07) :5476-5497
[2]   Blockchain Technology in Healthcare: A Systematic Review [J].
Agbo, Cornelius C. ;
Mahmoud, Qusay H. ;
Eklund, J. Mikael .
HEALTHCARE, 2019, 7 (02)
[3]   The state of play of blockchain technology in the financial services sector: A systematic literature review [J].
Ali, Omar ;
Ally, Mustafa ;
Clutterbuck ;
Dwivedi, Yogesh .
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2020, 54 (54)
[4]  
Alladi Tejasvi, 2020, Vehicular Communications, V23, DOI 10.1016/j.vehcom.2020.100249
[5]   Blockchain technology in the energy sector: A systematic review of challenges and opportunities [J].
Andoni, Merlinda ;
Robu, Valentin ;
Flynn, David ;
Abram, Simone ;
Geach, Dale ;
Jenkins, David ;
McCallum, Peter ;
Peacock, Andrew .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2019, 100 :143-174
[6]   Hyperledger Fabric: A Distributed Operating System for Permissioned Blockchains [J].
Androulaki, Elli ;
Barger, Artem ;
Bortnikov, Vita ;
Cachin, Christian ;
Christidis, Konstantinos ;
De Caro, Angelo ;
Enyeart, David ;
Ferris, Christopher ;
Laventman, Gennady ;
Manevich, Yacov ;
Muralidharan, Srinivasan ;
Murthy, Chet ;
Binh Nguyen ;
Sethi, Manish ;
Singh, Gari ;
Smith, Keith ;
Sorniotti, Alessandro ;
Stathakopoulou, Chrysoula ;
Vukolic, Marko ;
Cocco, Sharon Weed ;
Yellick, Jason .
EUROSYS '18: PROCEEDINGS OF THE THIRTEENTH EUROSYS CONFERENCE, 2018,
[7]  
[Anonymous], 2021, Investopedia
[8]  
[Anonymous], ARXIV
[9]   FedOpt: Towards Communication Efficiency and Privacy Preservation in Federated Learning [J].
Asad, Muhammad ;
Moustafa, Ahmed ;
Ito, Takayuki .
APPLIED SCIENCES-BASEL, 2020, 10 (08)
[10]   Poster: A Reliable and Accountable Privacy-Preserving Federated Learning Framework using the Blockchain [J].
Awan, Sana ;
Li, Fengjun ;
Luo, Bo ;
Liu, Mei .
PROCEEDINGS OF THE 2019 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY (CCS'19), 2019, :2561-2563