Generating Steganographic Text with LSTMs

Motivated by concerns for user privacy, we design a steganographic system ("stegosystem") that enables two users to exchange encrypted messages without an adversary detecting that such an exchange is taking place. We propose a new linguistic stegosystem based on a Long Short-Term Memory (LSTM) neural network. We demonstrate our approach on the Twitter and Enron email datasets and show that it yields high-quality steganographic text while significantly improving capacity (encrypted bits per word) relative to the state-of-the-art.


Published in:
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics - Student Research Workshop, 100-106
Presented at:
ACL Student Research Workshop 2017, Vancouver, Canada, July 30-August 4, 2017
Year:
2017
Laboratories:




 Record created 2017-07-11, last modified 2019-08-12

n/a:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)