Steganography in animated emoji using self-reference

Abstract Animated emoji is a kind of GIF image, which widely used in online social networks (OSN) for its efficiency transmitting vivid and personalized information. Aiming at realizing covert communication animated emoji, this paper proposes an improved steganography framework emoji. We propose self-reference algorithm to improve the security. Meanwhile, relations between adjacent frames cover image are considered further distortion function. After that we embed secret message into using popular Syndrome Trellis Coding (STC). Experimental results show proposed method can provide better security performances than state-of-the-art works.