2022 International Balkan Conference on Communications and Networking (BalkanCom) 2022
DOI: 10.1109/balkancom55633.2022.9900546
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Towards Blockchain-based Hierarchical Federated Learning for Cyber-Physical Systems

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Cited by 11 publications
(3 citation statements)
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“…Thus, 40 primary studies were selected for the SLR (see Table 4). 2022 P02 [77] 2020 P03 [78] 2022 P04 [79] 2022 P05 [80] 2023 P06 [81] 2023 P07 [82] 2020 P08 [83] 2022 P09 [84] 2023 P10 [85] 2022 P11…”
Section: B Conducting the Reviewmentioning
confidence: 99%
“…Thus, 40 primary studies were selected for the SLR (see Table 4). 2022 P02 [77] 2020 P03 [78] 2022 P04 [79] 2022 P05 [80] 2023 P06 [81] 2023 P07 [82] 2020 P08 [83] 2022 P09 [84] 2023 P10 [85] 2022 P11…”
Section: B Conducting the Reviewmentioning
confidence: 99%
“…In addition, federated learning faces the poisoning attack [105]; several works focus on analyzing participants' behavior using blockchain. Reference [106] introduced a blockchain-based hierarchical federated learning for cyber-physical systems, which employs the blockchain to verify and validate the trained models on the edge. Similarly, Al Mallah et al [107] devised a BCFL scheme, in which the miner in blockchain not only exchange local model update but also monitoring the behavior of all the participants to select reliabel devices.…”
Section: Bcfl In Internet Of Things (Iot)mentioning
confidence: 99%
“…Zhang et al [25] proposed a dynamic fusion-based FL for medical diagnosis to classify COVID-19 infections, which can adaptively determine the participants according to their local model performance and model aggregation scheme based on participants' training time. In 2022, Aloqaily et al [26] proposed a hierarchical federated learning (HFL) solution based on blockchain, which can provide fast, safe, and accurate decision making for industrial machines.…”
Section: Federated Learning-based Industrial Applicationsmentioning
confidence: 99%