Answers.Body: <p>The short answer is <code>No</code>.</p>
  <p>The long answer is <em><code>maybe</code></em>, if you use <a href="https://en.wikipedia.org/wiki/Homomorphic_encryption" rel="nofollow noreferrer">Homomorphic encryption</a>.</p>
  <blockquote>
  <p>Homomorphic encryption is the conversion of data into ciphertext that can be analyzed and worked with as if it were still in its original form. Homomorphic encryption enables complex mathematical operations to be performed on encrypted data without compromising the encryption.</p>
  </blockquote>
  <p>However, this is a very mathematically complex task, and the encryption is weak at best.</p>
  <blockquote>
  <p>Homomorphic encryption schemes are inherently <a href="https://en.wikipedia.org/wiki/Malleability_(cryptography)" rel="nofollow noreferrer">malleable</a>. In terms of malleability, homomorphic encryption schemes have weaker security properties than non-homomorphic schemes.</p>
  </blockquote>
  <hr />
  <p>Here's an <a href="https://developer.nvidia.com/blog/federated-learning-with-homomorphic-encryption/" rel="nofollow noreferrer">image</a> courtesy of Nvidia:</p>
  <p><a href="https://i.sstatic.net/AlbKk.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/AlbKk.png" alt="enter image description here" /></a></p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2023-11-23T13:02:17.283Z
Answers.LastActivityDate: 2023-11-23T13:10:40.040Z
Answers.LastEditDate: 2023-11-23T13:10:40.040Z
Answers.UserDisplayName: not2qubit
Body: <p>I wuold like to know if it is possible to train a CNN to classify images (like nsfw detection) without receiving any intelligible information about it ?</p>
  <p>By applying some kind of one-way mask before upload for example.</p>
  <p>Edit: I found that it is possible to apply filters on encrypted images with homomorphic encryption, but I don't know if classification is possible.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-11-20T00:39:59.310Z
Comments.Text: you can do density estimation if you manage to collect a dataset of only nsfw images
Comments.UserDisplayName: Alberto
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-11-20T16:04:34.320Z
Comments.Text: Hi @max-it and welcome to AI Stack Exchange! If possible, please edit this post to include a question in the title. Also, please add more detail to the question that might help people provide better answers. Thank you for participating, and we look forward to more of your questions in the near future!
Comments.UserDisplayName: DeepQZero
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-11-22T14:29:00.603Z
Comments.Text: To your edit, it would require that homomorphic encryption is used, which is not typical.
Comments.UserDisplayName: David Hoelzer
Tags: <machine-learning>
Title: Is it possible to do machine learning on encrypted images?
UserDisplayName: max-lt
ThreadText: # Is it possible to do machine learning on encrypted images?
  
  (Asked by: username_0 on 2023-11-20)
  
  I wuold like to know if it is possible to train a CNN to classify images (like nsfw detection) without receiving any intelligible information about it ?
  
  By applying some kind of one-way mask before upload for example.
  
  Edit: I found that it is possible to apply filters on encrypted images with homomorphic encryption, but I don't know if classification is possible.
  
  **Tags:** machine-learning
  > **Comments:**
  > **username_1**: you can do density estimation if you manage to collect a dataset of only nsfw images  
  > **username_2**: Hi @max-it and welcome to AI Stack Exchange! If possible, please edit this post to include a question in the title. Also, please add more detail to the question that might help people provide better answers. Thank you for participating, and we look forward to more of your questions in the near future!  
  > **username_3**: To your edit, it would require that homomorphic encryption is used, which is not typical.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_4 on 2023-11-23. Score: 1
  
  The short answer is `No`.
  
  The long answer is *`maybe`*, if you use [Homomorphic encryption](https://en.wikipedia.org/wiki/Homomorphic_encryption).
  
  > Homomorphic encryption is the conversion of data into ciphertext that can be analyzed and worked with as if it were still in its original form. Homomorphic encryption enables complex mathematical operations to be performed on encrypted data without compromising the encryption.
  
  However, this is a very mathematically complex task, and the encryption is weak at best.
  
  > Homomorphic encryption schemes are inherently [malleable](https://en.wikipedia.org/wiki/Malleability_(cryptography)). In terms of malleability, homomorphic encryption schemes have weaker security properties than non-homomorphic schemes.
  
  ---
  
  Here's an [image](https://developer.nvidia.com/blog/federated-learning-with-homomorphic-encryption/) courtesy of Nvidia:
  
  [![enter image description here](https://i.sstatic.net/AlbKk.png)](https://i.sstatic.net/AlbKk.png)
  
  
  ---
  
  