%0 Journal Article %1 https://doi.org/10.48550/arxiv.2210.07714 %A Rieger, Phillip %A Krauß, Torsten %A Miettinen, Markus %A Dmitrienko, Alexandra %A Sadeghi, Ahmad-Reza %D 2022 %I arXiv %J ArXiv | arXiv:2210.07714 %K Private_AI myown sss-group torstenkrauss %R 10.48550/ARXIV.2210.07714 %T Close the Gate: Detecting Backdoored Models in Federated Learning based on Client-Side Deep Layer Output Analysis %U https://arxiv.org/abs/2210.07714

@article{https://doi.org/10.48550/arxiv.2210.07714, added-at = {2022-10-17T15:12:31.000+0200}, author = {Rieger, Phillip and Krauß, Torsten and Miettinen, Markus and Dmitrienko, Alexandra and Sadeghi, Ahmad-Reza}, biburl = {https://www.bibsonomy.org/bibtex/2b019d6e29f6aba408405abb50cded8ef/sssgroup}, copyright = {arXiv.org perpetual, non-exclusive license}, doi = {10.48550/ARXIV.2210.07714}, interhash = {60ac3c48c60c2dcef502c7cdbbaa1d58}, intrahash = {b019d6e29f6aba408405abb50cded8ef}, journal = {ArXiv | arXiv:2210.07714}, keywords = {Private_AI myown sss-group torstenkrauss}, publisher = {arXiv}, timestamp = {2023-01-17T14:23:18.000+0100}, title = {Close the Gate: Detecting Backdoored Models in Federated Learning based on Client-Side Deep Layer Output Analysis}, url = {https://arxiv.org/abs/2210.07714}, year = 2022 }