From 7b9f97f703f9244615ceeee9001e99fd5e6ae5a3 Mon Sep 17 00:00:00 2001
From: Orson93 <64611605+OrsonTyphanel93@users.noreply.github.com>
Date: Sun, 22 Oct 2023 21:47:16 -0400
Subject: [PATCH 1/2] Update README.md

creation of an audio backdoor attack using stylistic transformations
---
 notebooks/README.md | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/notebooks/README.md b/notebooks/README.md
index 95806cbf65..4379b9bfb1 100644
--- a/notebooks/README.md
+++ b/notebooks/README.md
@@ -28,8 +28,10 @@ demonstrates the dirty-label backdoor attack on a TensorflowV2 estimator for spe
 <p align="center">
   <img src="../utils/data/images/adversarial_audio_waveform.png?raw=true" width="200" title="adversarial_audio_waveform">
 </p>
+  
+[stylistics_attack_backdoor_audio.ipynb](IEEE_OJSP_;_Backdoor_attack_using_audio_stylistic_transformations_in_deep_neural_network_model_learning.ipynb) [[on nbviewer](https://github.com/OrsonTyphanel93/Deep-Learning-Orson-/blob/master/IEEE_OJSP_%3B_Backdoor_attack_using_audio_stylistic_transformations_in_deep_neural_network_model_learning.ipynb)]
 
-## Adversarial training
+## Adversarial training  
 
 [adversarial_retraining.ipynb](adversarial_retraining.ipynb) [[on nbviewer](https://nbviewer.jupyter.org/github/Trusted-AI/adversarial-robustness-toolbox/blob/main/notebooks/adversarial_retraining.ipynb)]
 shows how to load and evaluate the MNIST and CIFAR-10 models synthesized and adversarially trained by 

From 239675d0ddd151eb3cf06fbae5c34171715c29dc Mon Sep 17 00:00:00 2001
From: Orson93 <64611605+OrsonTyphanel93@users.noreply.github.com>
Date: Sun, 22 Oct 2023 22:31:08 -0400
Subject: [PATCH 2/2] Update README.md

---
 notebooks/README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/notebooks/README.md b/notebooks/README.md
index 4379b9bfb1..917a37b685 100644
--- a/notebooks/README.md
+++ b/notebooks/README.md
@@ -29,7 +29,7 @@ demonstrates the dirty-label backdoor attack on a TensorflowV2 estimator for spe
   <img src="../utils/data/images/adversarial_audio_waveform.png?raw=true" width="200" title="adversarial_audio_waveform">
 </p>
   
-[stylistics_attack_backdoor_audio.ipynb](IEEE_OJSP_;_Backdoor_attack_using_audio_stylistic_transformations_in_deep_neural_network_model_learning.ipynb) [[on nbviewer](https://github.com/OrsonTyphanel93/Deep-Learning-Orson-/blob/master/IEEE_OJSP_%3B_Backdoor_attack_using_audio_stylistic_transformations_in_deep_neural_network_model_learning.ipynb)]
+[stylistics_attack_backdoor_audio.ipynb](Backdoor_attack_using_audio_stylistic_transformations_in_deep_neural_network_model_learning.ipynb) [[on nbviewer](https://github.com/OrsonTyphanel93/Deep-Learning-Orson-/blob/master/Backdoor_attack_using_audio_stylistic_transformations_in_deep_neural_network_model_learning.ipynb)]
 
 ## Adversarial training