Thien and Lin ͓Comput. and Graphics 26͑5͒, 765-770 ͑2002͔͒ proposed a threshold scheme to share a secret image among n shadows: any t of the n shadows can recover the secret, whereas t −1 or fewer shadows cannot. However, in real life, certain managers probably play key roles to run a company and thus need special authority to recover the secret in managers' meeting. ͑Each manager's shadow should be more powerful than an ordinary employee's shadow.͒ In Thien and Lin's scheme, if a company has less than t managers, then manager's meeting cannot recover the secret, unless some managers were given multiple shadows in advance. But this compromise causes managers inconvenience because too many shadows were to be kept daily and carried to the meeting. To solve this dilemma, a weighted sharing method is proposed: each of the shadows has a weight. The secret is recovered if and only if the total weights ͑rather than the number͒ of received shadows is at least t. The properties of GF͑2 r ͒ are utilized to accelerate sharing speed. Besides, the method is also a more general approach to polynomial-based sharing. Moreover, for convenience, each person keeps only one shadow and only one shadow index.
The stego-images generated by many existing hiding techniques are not economic in size, and hence need compression. Unfortunately, compression usually destroys the secret content hidden inside. To solve this dilemma, some hiding methods based on compression code (rather than the image itself) are reported. This paper proposes a high-capacity and high-hiding-ratio "reversible" steganography method based on JPEG-compression code. In the proposed method, the JPEG compression code of an image is used as the cover media. An 8×8 hiding-capacity table is firstly evaluated, which is then utilized to modify the quantization table attached to the given JPEG code. The two quantization tables (modified and original) together can map the DCT coefficients of each block to some larger DCT coefficients, with secret data hidden inside these larger DCT coefficients. In the decoding process, after lossless extraction of the hidden secret data, the proposed method can also recover the original JPEG-compression code. Experimental results show that our method outperforms other JPEG-based hiding methods (reversible or not) regarding both hiding-ratio and stego-image's quality.
We propose a multithreshold progressive reconstruction method. The image is encoded three times using Joint Photographic Experts Group (JPEG): first with a low-quality factor, then with a medium-quality factor, and last with a high-quality factor. Huffman coding is employed to encode the difference between the important image and the high-quality JPEG decompressed image. The three JPEG codes and the Huffman code are shared, respectively, according to four prespecified thresholds. The n-generated equally important shadows can be stored or transmitted using n channels in parallel. Cooperation among these generated shadows can progressively reconstruct the important image. The reconstructed image is loss-free when the number of collected shadows reaches the largest threshold. Each shadow is very compact and so can be hidden successfully in the JPEG codes of cover images to reduce the probability of being attacked when transmitted in an unfriendly environment. Comparisons with other image sharing methods are made. The contributions, such as easiness to apply to scalable Moving Picture Experts Group (MPEG) video transmission or resistance to differential attack, are also included.
Secure sharing of digital images is becoming an important issue. Consequently, many schemes for ensuring image sharing security have been proposed. However, existing approaches focus on the sharing of a single image, rather than multiple images. We propose three kinds of sharing methods that progressively reveal n given secret images according to the sensitivity level of each image. Method 1 divides each secret image into n parts and then combines and hides the parts of the images to get n steganographic (stego) JPEG codes of equal importance. Method 2 is similar; however, it allocates different stego JPEG codes of different 'weights' to indicate their strength. Method 3 first applies traditional threshold-sharing to the n secret images, then progressively shares k keys, and finally combines the two sharing results to get n stego JPEG codes. In the recovery phase, various parameters are compared to a pre-specified low/middle/high (L/M/H) threshold and, according to the respective method, determine whether or not secret images are reconstructed and the quality of the images reconstructed. The results of experiments conducted verify the efficacy of our methods.
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