Steganography, the art of concealing secret messages within other pieces of text or media, has been in practice for centuries. Its history dates to Ancient Greece, but the first recorded use of the term was in 1499 in a book disguised as a book about magic titled Steganographia. Even today, this method remains relevant, with people altering images to hide messages by changing pixels and encoding the information. A computer can then compare the two images and decipher the hidden message for the recipient.
However, traditional methods of using steganographic images have a significant flaw: an adversary can find the original image, making it possible to compare it with the image containing the hidden message. This comparison allows them to decode the message and potentially compromise the sender’s security. Luke Bauer, a Ph.D. student at the University of Florida conducting research at the Florida Institute of Cybersecurity Research (FICS), is working to eliminate this vulnerability by developing an innovative approach that leverages artificial intelligence (AI) image generation.
Bauer’s innovative research focuses on using AI to create images that already contain hidden messages, eliminating the need for a comparison between the original and encoded images. This means that a message sender can upload the hidden message to public platforms without arousing suspicion, making it difficult for an adversary to identify the post containing the encoded message. Meanwhile, the message receiver can decipher the hidden message using the same AI model, without requiring specialized software.