Reliable detection of LSB steganography in color and grayscale images

Abstract

A system and method that efficiently, accurately, and simply detect reliably least-significant-bit (“LSB”) embedding of a secret message in randomly scattered pixels. The system and method apply to both 24-bit color images and 8-bit grayscale or color images. Many commercial steganographic programs use Least Significant Bit embedding (LSB) as the method of choice to hide messages in 24-bit, 8-bit color images and in grayscale images. They do so based on the common belief that changes to the LSBs of colors cannot be detected because of noise that is always present in digital images. By inspecting the differences in capacity for lossless (invertible) embedding in the LSB and the shifted LSB plane, the present invention reliably detects messages as short as 1% of the total number of pixels (assuming 1 bit per sample). The system and method of the present invention are fast, and they provide accurate estimates for the length of the embedded secret message.

Description

STATEMENT OF GOVERNMENT INTEREST[0001]This invention was made with Government support under F30602-00-1-0521 and F49620-01-1-0123 from the U.S. Air Force. The Government has certain rights in the invention.BACKGROUND OF THE INVENTION[0002]This invention relates to steganography. Steganography is the art of secret communication, whose purpose is to hide the very presence of a communication. In particular this invention relates to the detection of hidden messages.[0003]Steganography differs from cryptography, whose goal is to make communication unintelligible to those who do not posses the right keys. By means of steganography, digital images, videos, sound files, and other computer files that contain perceptually irrelevant or redundant information can be used as covers, that is, as carriers that hide secret messages embedded within. If one embeds a secret message into a cover-image, one obtains a “stego-image.”[0004]The stego-image cannot contain any detectable artifacts that result...

AI Technical Summary

Benefits of technology

[0011]An object of the present invention is to provide an efficient, accurate, and simple method to reliably detect LSB embedding.

[0013]Still a further object of the present invention is to provide such a method to reliably detect LSB embedding where the randomly scattered pixels are in both 24-bit color images and 8-bit grayscale or color images.

[0014]Briefly stated, the present invention provides a system and a method that efficiently, accurately, and simply detect reliably least-significant-bit (“LSB”) embedding of a secret message in randomly scattered pixels. The system and method apply to both 24-bit color images and 8-bit grayscale or color images. Many commercial steganographic programs use Least Significant Bit embedding (LSB) as the method of choice to hide messages in 24-bit, 8-bit color images and in grayscale images. They do so based on the common belief that changes to the LSBs of colors cannot be detected because of noise that is always present in digital images. By inspecting the differences in capacity for lossless (invertible) embedding in the LSB and the shifted LSB plane, the present invention reliably detects messages as short as 1% of the total number of pixels (assuming 1 bit per sample). The system and method of the present invention are fast, and they provide accurate estimates for the length of the embedded secret message.

Problems solved by technology

Once the third party can reliably detect the presence of the secret message, the steganographic tool becomes useless.

Images stored in the JPEG format make very poor cover images for steganographic methods that embed information in the spatial (pixel) domain.

They do so because it is generally believed that changes to the LSBs of colors cannot be detected.

The results become progressively unreliable once the number of unique colors exceeds roughly 50% of the number of pixels, as happens frequently for high resolution raw scans and images taken with digital cameras stored in an uncompressed format.

Another disadvantage of the RQP method is that it cannot be modified for grayscale images.

However, randomly scattered messages can only be reliably detected with this method when the message length becomes comparable with the number of pixels in the image.

1525, Springer-Verlag, 1998) pointed out that steganographic methods for palette images that preprocess the palette can be vulnerable.

However, steganographic techniques that do not modify the palette (e.g., those that hide messages by embedding LSB into the pointers) cannot be detected by inspecting the palette itself.

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