Transactions on data hiding and multimedia security VI by Patchara Sutthiwan, Yun Q. Shi, Hong Zhao, Tian-Tsong Ng,
By Patchara Sutthiwan, Yun Q. Shi, Hong Zhao, Tian-Tsong Ng, Wei Su (auth.), Yun Q. Shi, Sabu Emmanuel, Mohan S. Kankanhalli, Shih-Fu Chang, Regunathan Radhakrishnan, Fulong Ma, Li Zhao (eds.)
Since the mid Nineties, info hiding has been proposed as an permitting expertise for securing multimedia verbal exchange, and is now utilized in quite a few purposes together with broadcast tracking, motion picture fingerprinting, steganography, video indexing and retrieval, and snapshot authentication. info hiding and cryptographic thoughts are usually mixed to counterpoint one another, hence triggering the advance of a brand new learn box of multimedia protection. in addition to, comparable disciplines, steganalysis and information forensics, are more and more attracting researchers and turning into one other new examine box of multimedia defense. This magazine, LNCS Transactions on information Hiding and Multimedia protection, goals to be a discussion board for all researchers in those rising fields, publishing either unique and archival examine effects. This factor is composed typically of a unique part on content material defense and forensics together with 4 papers. the extra paper bargains with histogram-based picture hashing for looking out content-preserving copies.
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Therefore, we give the experimental analysis, where we investigate if αi s are similar to αi s. In case αi s are higher than αi s, the entropy of the encrypted coeﬃcients will be more than in the case when they are equal, which leads to more rise in bpp. 1 0 0 20 40 60 Encryption range 80 100 Fig. 3. Increase in bpp for diﬀerent encryption ranges encryptions under diﬀerent QF’s. Figure 3 suggests that, the value of qlimit = 9, and α1 = 100, α2 = 10 and α3 = 1, while taking ζ = 3 gives minimum increase in bpp without compromising the security.
The hamming distance d(W ∗ , W o ) is expected to be suﬃciently small for the two similar sequences, whereas it is expected to be larger than a selected threshold for the two dissimilar sequences. Hence, the distribution of false acceptance rate (FAR) versus false rejection rate (FRR) can be obtained by varying the threshold values, as shown in Fig. 10. The results obtained by using a single high-pass frequency coeﬃcient are also included to demonstrate that using a single coeﬃcient to carry the watermark data does not work well.
Let K coef denotes the embedding key. K coef gives the exact position of the coeﬃcient which is to be watermarked. This can be generated from a random number generator in the range [0, N − 1] and dropping any repeated numbers, which can then act as an index to the coeﬃcients . Towards this, the ﬁrst R (≤ 6) AC coeﬃcients from each block are picked up in a zig-zag manner (as shown in ﬁg 2) and arranged in a 1-D array of N elements. Then the random number generator gives the index of the coeﬃcients in this array which are used for embedding.