• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권10호
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• pp.2514-2526
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• 2013

This paper presents a detection method for least significant bit matching revisited (LSBMR) steganography. Previous research shows that the adjacent pixels of natural images are highly correlated and the value 0 appears most frequently in pixel difference. Considering that the message embedding process of LSBMR steganography has a weighted-smoothing effect on the distribution of pixel difference, the frequency of the occurrence of value 0 in pixel difference changes most significantly whereas other values approximately remain unchanged during message embedding. By analyzing the effect of LSBMR steganography on pixel difference distribution, an equation is deduced to estimate the frequency of difference value 0 using the frequencies of difference values 1 and 2. The sum of the ratio of the estimated value to the actual value as well as the ratio of the frequency of difference value 1 to difference value 0 is used as the steganalytic detector. Experimental results show that the proposed method can effectively detect LSBMR steganography and can outperform previous proposed methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권6호
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• pp.1718-1734
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• 2012

The proposed method in this paper is derived from Mielikainen's hiding method. However, there exist some significant differences between two methods. In Mielikainen's method, pixels are partitioned into pairs and a LSB matching function is applied to two pixels for hiding. On the contrary, the proposed method partitions pixels into groups with three pixels in each group. The bits of pixels in each group are linked by using an exclusive OR (XOR) operator in a circular way. If the number of different values between the calculated XOR values and the secret bits is smaller than or equal to 2 in a group, the proposed method can guarantee that at most one pixel is needed to be modified by adding/subtracting its value to/from one, and three secret bits can be embedded to three pixels. Through theoretical analysis, the amount of the embedded secret data in the proposed method is larger than those in other methods under the same amount of pixel modifications. Taking real images in our experiments, the quality of stego-images in the proposed method is higher than those in other methods.