A more secure steganography based on adaptive pixel-value ...

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Multimed Tools Applare inevitably contaminated by such a random selection scheme, which will lead topoorer security performances <strong>based</strong> on our extensive experiments.5 Concluding remarksIn accordance with the limitations of the existing PVD-<strong>based</strong> schemes, an adaptiveand <strong>more</strong> <strong>secure</strong> steganographic method has been studied in the paper. Quitedifferent from typical PVD and it improved versions, whose embedding positionsare mainly determined by a PRNG without considering the relationship betweenthe image contents and the size of the message to be embedded. Our novel methodcan first embed secret bits at the sharper regions adaptively, while keeping thosesmooth/flat regions as they are. Besides that, the new method does not destroy sortrelationships between the three consecutive pixels within all the embedding units.In such a way, fewer visual artifacts and detectable artifacts will be introduced.The experimental results evaluated on a large image database show the significantimprovements in terms of adaptability and security compared with the existing ones.In the future step, we will investigate whether our proposed idea can be applied toother steganographic schemes that in the frequency domain for enhancing security.Acknowledgements This work is supported by the NSFC (60633030), 973 Program(2006CB303104), China Postdoctoral Science Foundation (20080440795), Funds of Key Labof Fujian Province University Network Security and Cryptology (09A011) and Guangzhou Scienceand Technology Program (2009J1-C541-2).AppendixFigure 8 illustrates the four different cases according to the pixel values g i , g i+1 , g i+2within an embedding unit and a given threshold T. Note that g i and g i+2 are fixedbefore and after data embedding. In this appendix, we want to show you how todetermine the range of the centre pixel values range g ′i+1so that the sort order of thethree consecutive pixel values and the relationships between the pixel values and Tare well preserved after data embedding.gi+2gi+1TgiTgi+2giTgi+1(a) Case 1gi(b) Case 2gi+2gi+1TT(c) Case 3gi+2gigi+1T(d) Case 4Fig. 8 Four different cases according to the values of g i , g i+1 , g i+2
Multimed Tools ApplWithout loss of generality, case 1.1 is considered. Other cases can be analyzed ina similar way. In case 1.1,we have the following inequations:∣ ∣ ∣g i+1 < g i , g i+1 < g i+2 , ∣ d1 > T, ∣d2 > TThen we obtain∣ d1∣ ∣ =∣ ∣gi − g i+1∣ ∣ = gi − g i+1 > T,Namely∣ d2∣ ∣ =∣∣gi+1 − g i+2∣ ∣ = gi+2 − g i+1 > Tg i+1 < g i − T, g i+1 < g i+2 − TSince g i+1 is an integer and belongs to [0,...,255], we can obtaing i+1 ∈ [ 0,...,min ( g i − T − 1, g i+2 − T − 1 )]Therefore, if we limit the centre pixel value changing in the following range whendoing data embeddingrange g ′i+1=[0,...,min(g i − T − 1, g i+2 − T − 1)]All the inequations in case 1.1 will hold. And this is very important to preservesome local structure features in the cover image. However, most existing PVD-<strong>based</strong>approaches will inevitably destroy such relationships and thus make it easy to detect<strong>based</strong> on the extensive experiments.Moreover, it can be seen that the range is constrained by a threshold T. Usually,the larger the threshold T is, the narrower the range is, and thus the fewer secretbits can be embedded using our proposed method. In practice, we can change thethreshold T to adjust the embedding capacity. For the short secret message, we canjust use those pixels on the sharper edges (larger than T) within an image for datahiding, while keep other smooth regions (smaller than or equal to T) unchanged.If there is not enough space for the given secret message, we will decrease thethreshold T to enlarge the embedding space. In such a way, our method is <strong>more</strong>adaptive with image contents. Based on our experiments and analysis, both the visualimperceptivity and security will become much better.Please note that since all the inequations are preserved after data embedding, wecan reappear the same range in the stego image, which guarantees the validity of dataextraction.References1. Chan CK, Cheng L-M (2004) Hiding data in images by simple LSB substitution. Pattern Recogn37:469–4742. Farid H (2002) Detecting hidden messages using higher-order statistical models. In: IEEE int.conf. on image processing, vol 2, pp II905–II9083. Huang F, Li B, Huang J (2007) Attack LSB matching <strong>steganography</strong> by counting alterationrate of the number of neighbourhood gray levels. In: IEEE international conference on imageprocessing, vol 1, pp 401–4044. Ker AD (2005) Steganalysis of LSB matching in grayscale images. IEEE Signal Process Lett12(6):441–4445. Lee YK, Chen LH (2000) High capacity image steganographic model. In: Proceedings of IEEinst. elect. eng., vis. images signal process, vol 147, pp 288–294
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