title: Using Autoencoder on numerical dataset in Keras
body: <p>I am trying to develop an Intrusion Detection System based on deep learning using Keras.</p>
  
  <p>We simulated a NORMAL network traffic and I prepared it in CSV file (numerical dataset of network packets fields (IP source, port,etc..)). But I do not have the ABNORMAL (malicious) packets to train the neural network on.</p>
  
  <p>I searched for problems like that and I found that Autoencoder is a good approach in unsupervised learning, but the thing is that I am new to deep learning, and I only found this example <a href="https://blog.keras.io/building-autoencoders-in-keras.html" rel="nofollow noreferrer">https://blog.keras.io/building-autoencoders-in-keras.html</a> where they are using Autoencoder on images dataset.</p>
  
  <p>I want to use Autoencoder (or any thing useful in my case) with numerical CSV dataset in order to predict if the incoming packet is normal or malicious.</p>
  
  <p>Any recommendation?</p>