  In order to keep the data secret, various techniques have been implemented to
encrypt and decrypt the secret data. Cryptography is committed to the security
of content, i.e. it cannot be restored with a given ciphertext. Steganography
is to hiding the existence of a communication channel within a stego. However,
it has been difficult to construct a cipher (cypher) that simultaneously
satisfy both channel and content security for secure communication. Inspired by
the Cardan grille, this paper presents a new generative framework for grille
cipher. A digital cardan grille is used for message encryption and decryption.
The ciphertext is directly sampled by a powerful generator without an explicit
cover. Message loss and prior loss are proposed for penalizing message
extraction error and unrealistic ciphertext. Jensen-Shannon Divergence is
introduced as new criteria for channel security. A simple practical data-driven
grille cipher is proposed using semantic image inpainting and generative
adversarial network. Experimental results demonstrate the promising of the
proposed method.
