# PPSS: A privacy-preserving secure framework using blockchain-enabled federated deep learning for Industrial IoTs

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/ppss-a-privacy-preserving-secure-framework-using-blockchain-enabled-federated/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Djallel Hamouda,Mohamed Amine Ferrag,Nadjette Benhamida,Hamid Séridi |
| Citations | 53 |
| DOI | 10.1016/j.pmcj.2022.101738 |
| Fields | Computer Science,Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4312156850 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Hamid Séridi](https://scholariq.org/researchers/hamid-seridi/)

## Paper primary topic

- [Privacy-Preserving Technologies in Data](https://scholariq.org/topics/privacy-preserving-technologies-in-data/)

## Paper topics

- [Privacy-Preserving Technologies in Data](https://scholariq.org/topics/privacy-preserving-technologies-in-data/)
- [Blockchain Technology Applications and Security](https://scholariq.org/topics/blockchain-technology-applications-and-security/)
- [Smart Grid Security and Resilience](https://scholariq.org/topics/smart-grid-security-and-resilience/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.