Skip to content

Mimicking symmetric cryptosystem using adversarial networks to show that neural nets are able to learn to communicate with each other securely

Notifications You must be signed in to change notification settings

VamshikShetty/adversarial-neural-cryptography-tensorflow

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

11 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Adversarial Neural Cryptography

alt text

orginal paper : Learning to protect communications with adversarial neural cryptography

medium article

Training parameters:

learning_rate   = 0.0008
batch_size      = 4096
sample_size     = 4096*5 # 4096 according to the paper
epochs          = 10000  # 850000 according to the paper
steps_per_epoch = int(sample_size/batch_size)


# Input and output configuration.
TEXT_SIZE = 16
KEY_SIZE  = 16

# training iterations per actors.
ITERS_PER_ACTOR = 1
EVE_MULTIPLIER = 2  # Train Eve 2x for every step of Alice/Bob

Training Loss:

First 300 epochs

alt text

Last 300 epochs

alt text

About

Mimicking symmetric cryptosystem using adversarial networks to show that neural nets are able to learn to communicate with each other securely

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages