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On the Security Privacy in Federated Learning
[article]
2022
arXiv
pre-print
Recent privacy awareness initiatives such as the EU General Data Protection Regulation subdued Machine Learning (ML) to privacy and security assessments. Federated Learning (FL) grants a privacy-driven, decentralized training scheme that improves ML models' security. The industry's fast-growing adaptation and security evaluations of FL technology exposed various vulnerabilities that threaten FL's confidentiality, integrity, or availability (CIA). This work assesses the CIA of FL by reviewing
arXiv:2112.05423v2
fatcat:qcovp2cz2rfgbcvx6mtx5xighe