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@@ -68,7 +68,7 @@ Reconstruction attacks cover also attacks known as *model inversion* and *attrib
 
 ## Model extraction
 - [**Stealing machine learning models via prediction apis**](https://www.usenix.org/system/files/conference/usenixsecurity16/sec16_paper_tramer.pdf) (Tramèr et al., 2016) ([code](https://github.com/ftramer/Steal-ML)) 
-- [**Stealing hyperparameters in machine learning**](https://ieeexplore.ieee.org/iel7/8418581/8418583/08418595.pdf)(Wang B. et al., 2018)
+- [**Stealing hyperparameters in machine learning**](https://ieeexplore.ieee.org/iel7/8418581/8418583/08418595.pdf) (Wang B. et al., 2018)
 - [**Copycat CNN: Stealing Knowledge by Persuading Confession with Random Non-Labeled Data**](https://ieeexplore.ieee.org/document/8489592) (Correia-Silva et al., 2018) ([code](https://github.com/jeiks/Stealing_DL_Models))
 - [**Towards reverse-engineering black-box neural networks.**](https://openreview.net/forum?id=BydjJte0-)(Oh et al., 2018) ([code](https://github.com/coallaoh/WhitenBlackBox))
 - [**Knockoff nets: Stealing functionality of black-box models**](http://openaccess.thecvf.com/content_CVPR_2019/papers/Orekondy_Knockoff_Nets_Stealing_Functionality_of_Black-Box_Models_CVPR_2019_paper.pdf) (Orekondy et al., 2019) ([code](https://github.com/tribhuvanesh/knockoffnets))