A Prediction Mode-Based Information Hiding Approach for H.264/AVC Videos Minimizing the Impacts on Rate-Distortion Optimization

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1 A Prediction Mode-Based Information Hiding Approach for H.264/AVC Videos Minimizing the Impacts on Rate-Distortion Optimization Yu Wang 1,2(B), Yun Cao 1,2, Xianfeng Zhao 1,2, and Linna Zhou 3 1 State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing , China {wangyu9078,caoyun,zhaoxianfeng}@iie.ac.cn 2 School of Cyber Security, University of Chinese Academy of Sciences, Beijing , China 3 School of Information Science and Technology, University of International Relations, Beijing , China zhoulinna@mail.tsinghua.edu.cn Abstract. In this paper, with the data representation named intra prediction mode (IPM), an effective data hiding approach, called MIRO, integrated with H.264/AVC compression is proposed. The main principle is to minimize the embedding impacts on the video coding efficiency. First, a novel distortion function of individual IPM is designed reflecting its impact on Rate-Distortion Optimization. Secondly, the embedding structure based on syndrome-trellis codes (STCs) and interleaved sub-lattices are leveraged to minimize the overall embedding distortion. Comparative experimental results have demonstrated that, with similar embedding rates, the proposed method has much lower impacts on coding efficiency (both on the visual quality and compression efficiency) compared to other schemes. Keywords: Information hiding H.264/AVC Intra prediction Ratedistortion 1 Introduction The booming of H.264/advanced video coding (AVC) [1] has created an urgent need to explore the approaches of information hiding to restrict the illegal use of digital video. This paper targets the internal dynamics of video compression, specifically the intra-prediction stage. In literature, most methods of this type perform data hiding by changing the optimal intra prediction modes (IPMs) to suboptimal ones. In [2], a blind robust watermarking algorithm for H.264/AVC is proposed based on the idea of IPM modulation. Hu et al. [3] pointed out that the IPM of H.264/AVC is a suitable venue to hide message and proposed an algorithm by modifying intra 4 4 prediction modes (I4PMs) based on the mapping between c Springer International Publishing AG 2017 C. Kraetzer et al. (Eds.): IWDW 2017, LNCS 10431, pp , DOI: /

2 164 Y. Wang et al. I4PMs and hiding bits. Since then, a considerable number of IPM-based information hiding algorithms have been proposed. Yang et al. [4] applied matrix coding to improve the embedding capacity and control the increase of bit rate. Two watermark bits are mapped to every three I4PMs and only one I4PM is changed for two watermark bits. In [5], a data hiding scheme based on inter and intra prediction modes was proposed by means of constraining the prediction modes on different block sizes so the watermark bits of 0 and 1 can be effectively hidden. Xu et al. [6] proposed that marcroblocks were selectively chosen based on a chaotic sequence and one mode can carry one bit. To enhance security, the secret message is encrypted and blocks are selected randomly. For some real-time applications, Kapotas et al. [7] exploited the IPCM encoded macroblocks during the intra prediction stage in order to hide the desired data. This scheme doesn t considerably affect either the bit rate or perceptual quality, but it has a low embedding capacity indeed. Bouchama et al. [8] presented a new approach of exploiting I4PMs to increase data hiding capacity. I4PMs are divided into four groups composed of modes of close prediction directions. The data embedding is to modify modes of the same group in order to maintain both visual quality and capacity. Note that each IPM is a result of Rate-Distortion Optimization, any modulation will destroy its optimality. To make matters worse, because the intraprediction is highly interlaced, arbitrary modification will affect later coding processes that cannot be controlled [9]. It has been noticed that for the existing IPM-based approaches, no effective mechanism is available to suppress the embedding impact on the coding efficiency. The main contribution of this paper is to provide a solution to solve the problem of minimizing the overall embedding impacts on both the visual quality and compressional efficiency. First, a novel distortion function of individual IPM is designed reflecting its impact on Rate-Distortion Optimization. Secondly, using STCs implemented in a Gibbslike manner [10], messages are embedded minimizing the overall embedding distortion. The rest of this paper is organized as following. In Sect. 2, the H.264 intraprediction and the framework of distortion minimization are introduced. In Sect. 3, a novel distortion function reflecting the embedding impacts on Rate- Distortion Optimization is designed. And the procedure of adaptive embedding using STCs and interleaved sublattices is presented in details to show how to minimize the overall embedding impacts. In Sect. 4, comparative experiments are conducted to demonstrate the effectiveness of the proposed approach. Finally, the conclusions are given in Sect Preliminaries 2.1 Intra-Prediction in H.264/AVC In video coding standard H.264/AVC, intra-prediction is utilized to reduce the spatial redundancy and a higher compression ratio has been proved to be achieved for I-frame where all macroblocks have to be encoded in intra-modes

3 A Prediction Mode-Based Information Hiding Approach 165 Fig. 1. The predicted and reference samples for 4 4 luminance blocks containing 9 I4PMs and 4 intra prediction modes (I16PMs). I4PMs are used to characterize the regions with complicated texture of a picture and suited for coding parts of significant details. In contrast with I4PM, I16PMs are more suited for coding smooth areas of a picture. In all existing IPM-based algorithms, only I4PMs are modulated to carry hidden message. As illustrated in Fig. 1, there are 16 samples {a p} to be predicted in current 4 4 luminance block using the neighbor samples {A M}, after encoded and reconstructed, located in adjacent luminance blocks. To decrease the spatial redundancy, predictive coding is adopted to encode each residual of the sample. After traversal of 9 prediction modes in Fig. 2, the optimal mode (OPM) decision is performed by following R-D function J(s, c, IMODE QP, λ IMODE )=SSD(s, c, IMODE QP ) + λ MODE R(s, c, IMODE QP ) (1) where IMODE J is represented as one of IPMs in the current 4 4 luminance block. Here, J = {0,...,8} denotes the set of all 9 prediction modes for 4 4 Fig. 2. The 4 4 intra prediction modes

4 166 Y. Wang et al. luminance blocks. QP is the quantization parameter that is also utilized to compute the Lagrange multiplier λ MODE for mode decision, approximated as λ MODE = (QP 12)/3 (2) R is the required number of bits to encode the luminance block, mainly containing the bits of encoding IPM and transformed coefficients. SSD is the sum of squared differences between the original sample value s and the reconstructed sample value c as followed SSD = s(i, j) c(i, j) 2 (3) 1 i,j 4 Practically, the bits, required to encode the prediction mode, account for a large proportion in the total number of bits of 4 4 luminance blocks. For the current block C, as shown in Fig. 3, the most probable mode MPM C is estimated from the spatial adjacent modes of both left block A and upper block B as followed MPM C = min{mode left A, Mode upper B } (4) Mode left A and Modeupper B are the prediction modes of previously encoded 4 4 luminance block A and B respectively. Faced with the phenomenon that either left block A or upper block B is unavailable, the corresponding value of MPM C is set to 2(DC Mode). Fig. 3. Current and adjacent 4 4 luminance blocks There are two syntax elements called pred intra4 4 pred mode flag(pred) and rem intra4 4 pred mode(rem) introduced in the coding standard of H.264/AVC to encode the OPM. The identifier pred is denoted as the following pred = δ(opm, MPM C ) (5) { 1, x = y here the δ(, ) is defined as δ(x, y) =.Ifpred is set to 1, which means 0, x y that MPM is equal to OPM, only one bit is needed to encode pred and ignore the rem. While MPM and OPM are different, pred is set to 0 that indicates extra three bits are needed to encode the flag rem. { OPM, OPM < MPMC rem = (6) OPM 1, OPM > MPM C

5 A Prediction Mode-Based Information Hiding Approach Framework of Distortion Minimization For concreteness, and without loss of generality, we call a single intra-frame F with m n intra-prediction modes P as the cover frame. p p 1,1 p 1,2... p 1,n 1 P =. p 2,1 p 2,2... p 2,n. = X J m n (7) p m p m,1 p m,2...p m,n is a regular lattice of 4 4 luminance block s IPM, p i,j J,i M,j N, M = {1,...,m}, N = {1,...,n}. Since the IPMs are used as the data representation, F can be represented by P. With a given relative payload α, aαmn-bit message m is expected to be embedded by introducing modifications to IPMs in P, and the resultant stego frame is expressed as p p 1,1 p 1,2... p 1,n 1 P = p 2,1 p 2,2... p 2,n. = p (8) m p m,1 p m,2...p m,n In additive framework, the modifications are assumed to be mutually independent, and let every p i,j be assigned a scalar ρ i,j expressing the distortion of replacing it with p i,j, the overall embedding impact can be measured by the sum of per-element distortions D(P, P )= m i=1 j=1 n ρ i,j δ(p i,j,p i,j), (9) In order to achieve a minimal distortion with the given payload, a flexible coding method named STCs can be leveraged to guide the embedding process. In fact, STCs are a kind of syndrome coding with which the embedding and extraction can be formulated as Emb(P, m) = arg min D(P, P(P ) C(m) P ), (10) Ext(P )=HP(P ). (11) Here, P : J {0, 1} can be any parity check function, and P(P) = (P(p 1 ),...,P(p m )) T. H is a parity-check matrix of the code C, andc(m) is the coset corresponding to syndrome m. In more detail, H {0, 1} αmn mn is formed from a sub-matrix Ĥ {0, 1}h w, where h (called the constraint height) is a design parameter that affects the algorithm speed and efficiency and w is dictated by the desired relative payload α [11].

6 168 Y. Wang et al. 3 The Proposed Information Hiding Approach 3.1 Interaction of Predictive Coding For most the existing approaches, e.g., [3 6], IPMs are modified without considering the potential risk of distortion drift. Distortion drift is a typical side effect because the block-based intra prediction is highly correlated. To our best knowledge, these approaches cannot deal with interaction among embedding changes. As a result, the impacts on the coding efficiency cannot be properly controlled. To demonstrate the mutual influence, the process of how a single IPM modulation affects subsequent block codings is explained as follows. Definition 1. (Polluted Block). After changing the intra prediction mode of one 4 4 luminance block, if nothing else to be done, the latter block, whose mode cannot be decoded correctly, is defined as a polluted block. Fig. 4. Illustration of polluted blocks As introduced in Sect. 2, the identifier pred is used to indicate whether the current block s IPM is to be predicted according to the IPMs of its neighbors. if the lower block s or the right block s pred is set to 1, the perturbation of IPM of current block will propagate to its neighbors. As shown in Fig. 4, a8 8 block, comprised of four adjacent 4 4 blocks, is taken from an intra-frame of H.264 stream named crowd run, with the hope of depicting the polluted blocks. The IPMs of blocks with thick red solid lines are perturbed artificially and the blocks with red dotted lines represent the polluted blocks. The numbers labeled on each blocks are the value of IPMs. What intrigues us is that these polluted blocks are induced by just the perturbation of some blocks, any of whose identifier pred is equal to 0. In the previous work, the blocks with the

7 A Prediction Mode-Based Information Hiding Approach 169 identifier pred = 0 are recognized as the ones causing less distortion and suitable for embedding. However, without consideration of inducing polluted blocks, the appearance of decoding incorrectly is tremendously unacceptable owing to the existence of distortion drift. It is worth mentioning that, to solve the problem, there is an easy way by setting pred to 0 and re-coding the flag rem of the lower and right blocks of polluted blocks. If so, rate-distortion cost is suboptimal for not capturing the interaction among embedding changes, which requires a new distortion function with considering predictive coding. 3.2 Distortion Definition Under the framework of described in Sect. 2.2, assuming that modification is mutually independent, the scalar ρ i,j assigned to every p i,j P is expected to express the embedding impact. The overall embedding impact can be measured by the sum of per-element impact. It is a primary problem of designing the scalar ρ i,j, utilized to emerge both per-element independent distortion and the interaction among elements caused by predictive coding. In order to clarify the ρ i,j from both aspects, we introduce two concepts intra embedding impact and inter embedding impact. Definition 2. (Intra and Inter Embedding Impact). After changing the intra prediction mode of a 4 4 luminance block, the distortion used to measure embedding impact for this block, is defined as intra embedding impact. After changing the intra prediction modes of neighbors of a 4 4 luminance block, the distortion used to measure overall embedding impact for this block, is defined as inter embedding impact. Putting aside inter embedding impact, in general, we can use the ratedistortion cost to describe intra embedding impact of each block. Suppose that p i,j in the cover P is flipped to be p i,j, J(p i,j) andj(p i,j ) are the R-D cost of p i,j and p i,j respectively. Then, the scalar σ i,j, used to express the intra embedding impact, is obtained as followed σ i,j = min{j(p i,j) J(p i,j ) p i,j J, P(p i,j) P(p i,j )}. (12) For videos of H.264/AVC, R-D cost, adopted for mode decision, is proved to be a good way of measuring both the difference, between original and reconstructed samples, and the bits of encoding residuals and modes. It ignores the mutual influence between different blocks to get a low complexity of computing. The R-D optimization cannot reach the point of global optimum in theory but get a satisfactory result with near-global optimum in practice. For this, σ i,j is introduced to represent the intra embedding impact with purpose of minimizing the perturbation of R-D cost. To capture the mutual influence between adjacent blocks, we assign a scalar γ i,j to express the inter embedding impact, defined as the following γ i,j = S(p i 1,j+1,p i,j,p i,j+1,p i+1,j 1,p i+1,j ). (13)

8 170 Y. Wang et al. To illustrate the inter embedding impact, a more specific Fig. 5 is shown consisting of four subgraphs. After embedding, the extra distortion of current block pi,j caused by predictive coding, results from the different conditions of the lower block pi+1,j or the right block pi,j+1 referring to pi,j. For both pi+1,j and pi,j+1, each is required to be either choosing pi,j as the reference or not. The solid arrow depicts the relationship between neighbor blocks that one uses another as the prediction mode. Having the same effect, besides, the dotted arrow can be also used to express mutual independence between neighbors. Furthermore, we can get S(pi 1,j+1, pi,j, pi,j+1, pi+1,j 1, pi+1,j ) = δ(p i+1,j, 1) + δ(p i,j+1, 1) p i+1,j = δ(pi,j, MPMi+1,j ) [pi+1,j 1 0] = δ(pi,j, min{pi,j, pi+1,j 1 }) [pi+1,j 1 0] p i,j+1 = δ(pi,j, MPMi,j+1 ) [pi 1,j+1 0] = δ(pi,j, min{pi 1,j+1, pi,j }) [pi 1,j+1 0]. (14) (15) (16) Fig. 5. Schematic diagram of measuring inter embedding impact Here the Iverson bracket [I] is defined to be 1 if the logical expression I is true and 0 otherwise. MPMi,j is denoted as the most probable mode of pi,j, computed by pi,j 1 and pi 1,j, shown in Eq. (4). To guarantee pi,j 1 and pi 1,j available, used to obtain the value of MPMi,j, both pi,j 1 and pi 1,j are subject to be equal or greater than zero and otherwise MPMi,j is set to be negative resulting in p i,j set to 0, {, }. In this way, the scalar γi,j can be used to reflect the importance of pi,j, referred to by pi,j 1 and pi 1,j. When pi,j is

9 A Prediction Mode-Based Information Hiding Approach 171 used as the reference by more blocks, γ i,j will be assigned to be a larger value and verse vice. Since we get σ i,j and γ i,j, used to measure both intra embedding impact and inter embedding impact, the distortion function ρ i,j can be defined as followed ρ i,j = μσ i,j + βγ i,j (17) where μ and β are controllable factors. 3.3 The Procedure of Embedding and Extraction Based on the given distortion function, the practical implement of proposed method is introduced in this part. For measuring embedding impact, ρ i,j seems to be a favorable variable as the distortion function. However, since γ i,j has the form of a sum of locally supported potentials, if ρ i,j is applied for practical implement using STCs for data embedding, adjacent blocks are obviously inappropriate to be used as the cover at the same time. To resolve the problem, the embedding is implemented using Gibbs-like construction [10] on two interleaved sublattices, shown in Fig. 6. Divide the cover P into two parts P = P 1 P 2. The element of P 1 is represented by a solid dot and the element of P 2 is represented by a hollow square. Respectively, they are defined as the following form P 1 = {p i,j mod(i + j, 2) = 0} (18) P 2 = {p i,j mod(i + j, 2) = 1}. (19) With the support of Gibbs-like construction, two parts P 1 and P 2 alternate adaptive embedding for several times using STCs. Furthermore, to reduce the complexity of computing, for procedure of practical embedding, we need to rewrite it as followed ρ t,l i,j = μσt,l i,j + βγt 1, l i,j (20) where t is the meaning of t(th) time for embedding, l L= {1, 2}, and l is the complement element of l, l l = L, since L = 2 is binary. The distortion ρ t,l i,j, represented by a new form, is mainly to express that the intra embedding impact σ t,l i,j is obtained at the t(th) time computing ρt,l i,j of p i,j P l but the Fig. 6. Tessellation of the cover P into two disjoint sublattices P 1 and P 2

10 172 Y. Wang et al. Algorithm 1. Alternate embedding with single intra-frame Require: Input P, ρ, α, Ĥ, K and m Ensure: Output P 1: Encrypt message m with the private key K, m = Enc(K, m) 2: Divide m into two parts m 1 and m 2, m =[m 1 m 1] 3: Obtain two parts of P, P 1 and P 2, using (18) and (19) 4: Construct the mapping cover channel of intra prediction modes, x = P(P) ={x i,j x i,j = p i,j mod 2, 1 i m, 1 j n} 5: Initial y = x, y = y 1 y 2, y 1 = P(P 1), y 2 = P(P 2), t =1 6: Generate the STCs parity check matrix H with α and Ĥ; 7: Compute γ t 1,2 i,j for all y i,j y 1 using all y i,j y 2 8: for k =1tonumber of sweeps do 9: for l =1to2do 10: Execute for all y i,j y l 11: Compute σ t,l i,j for all cover y l using (12), γ t,l i,j for all cover y l using (14 16) 12: Obtain ρ i,j for all cover y l using (20) 13: y l = STC(y l,ρ,m l ), and record the places of perturbation 14: Flip all p i,j P l according to the records 15: t = t +1 16: end for 17: end for 18: Obtain P = P 1 P 2 inter embedding impact γ t 1, l i,j has been already obtained at the t 1(th) time computing the ρ t 1, l i,j of p i,j P l. The details are given in Algorithm 1. The retrieval of hidden information is simple and fast. After decoding IPMs of an intra-frame of the H.264/AVC video, we can get a sequence of IPMs that are further processed into two parts as described in Algorithm 2. Using (11), we can extract the encrypted message and the secret message is obtained by the decryption with the key K. Algorithm 2. Extraction with single intra-frame Require: Input P, Ĥ, andk Ensure: Output m 1: Divide P into two parts, P 1 and P 2, using (18) and (19) 2: Obtain y 1 and y 2, respectively, y 1 = P(P 1), x 2 = P(P 2), 3: Generate the STCs parity check matrix H with α and Ĥ; 4: m 1 = Hy 1 ; 5: m 2 = Hy 2 ; 6: m =[m 1 m 2] 7: Decrypt m and get message m = Dec(K, m )

11 4 Experiment 4.1 Experiment Setup A Prediction Mode-Based Information Hiding Approach 173 The proposed information hiding approach has been implemented in the H.264/AVC JM-19.0 reference software version The mainline profile is used in compression supporting I, P and B frames. In Fig. 7, the 14 video sequences in the 4: 2: 0 YUV (CIF, ) are selected to be test sequences with an intra-period of 12 at the frame rate of 30 frame per second. The number of each frame varies from 90 to 600. To implement our proposed scheme using a good STCs listed in [11], the constraint height h is set to 7 with the relative payload α {0.1, 0.25, 0.5}. To evaluate the effectiveness of the proposed approach, two typical IPM-based information hiding algorithms, i.e., Xu s [6] and Yang s [4] are completed to produce stego video sets, which are denoted as Alg 1 and Alg 2. The peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) are calculated compared to the original frames of the corresponding YUV files. If PSNR or SSIM is larger, which is affected by the value of QP, the visual quality is expected to be better. When the value of SSIM is generally to be above 0.9, perceptual quality is believed to be good. Since the bit-rate increase is dependent on the embedded capacity, in order to perform a fair comparison, we define the bit-rate increase ratio (BIR) as followed BIR = R e R o 100% (21) R o where R e denotes the bit-rate of the embedded video and R o denotes the bit-rate of the original video. Fig. 7. Test sequences 4.2 Performance Results and Analysis In Table 1, the test sequences are encoded with QP = 28 and relative payload α is equal to 0.1, 0.25 and 0.5. Comparing three algorithms in terms of average PSNR, SSIM and BIR, under the same relative payload α, three methods all perform good imperceptibility since each SSIM is above 0.94 and the modification of PSNR is very small, close to each other. But MIRO shows a better performance in average BIR which means that maintaining the similar visual quality, MIRO has much lower impacts on coding efficiency, especially the compression efficiency.

12 174 Y. Wang et al. With combination of Tables 1 and 2, as the same test sets being encoded with different QP, i.e., 28 and 32, we can see that, though the BIR of each method is increased, the BIR of MIRO is obviously smaller than that of Alg 1 or Alg 2. Besides, when QP is a larger value and the inter embedding impact is more significant, the BIR of Alg 1 or Alg 2 is much increased without considering the interaction between IPMs. Table 1. Performance comparison of different information hiding methods (QP = 28, GOP Size = 12). Method Relative payload PSNR(dB) SSIM BIR(%) Alg Alg MIRO Table 2. Performance comparison of different information hiding methods(qp = 32, GOP Size = 12). Method Relative payload PSNR(dB) SSIM BIR(%) Alg Alg MIRO According to three different video sequences (tractor, tennis and stockholm), each containing 300 frames, PSNR and BIR of three methods are specifically compared in Fig. 8. With a larger value of QP, MIRO has achieved a better result for minimizing the embedding impacts. From Fig. 8(a), (b) and (c), three methods all get good visual quality and MIRO is slightly superior to others. Referring to Fig. 8(d), (e) and (f), MIRO is obviously seen with the better compression efficiency since its BIR is much lower.

13 A Prediction Mode-Based Information Hiding Approach Alg 1 Alg Alg 2 MIRO 2.5 Alg 2 MIRO 2 PSNR(dB) BIR(%) Frame No. (a) Frame No. (b) 37 Alg 1 3 Alg Alg 2 MIRO 2.5 Alg 2 MIRO PSNR(dB) 36.8 BIR(%) Frame No Frame No. (c) (d) Alg 1 Alg 2 MIRO 2.5 Alg 1 Alg 2 MIRO PSNR(dB) BIR(%) Frame No. (e) Frame No. (f) Fig. 8. Performance comparison of different information hiding methods. (a), (c), (e) the curve of PSNR with QP = 24, 28, 32. (b), (d), (f) the curve of BIR with QP = 24, 28, Conclusion This paper presents a video information hiding approach tightly combined with H.264 compression, which uses the data representation called IPM to convey hidden messages. To minimize the embedding impacts on both the visual quality and compression efficiency, we define a novel distortion function of individual IPM reflecting its impact on Rate-Distortion Optimization and leverage an

14 176 Y. Wang et al. embedding structure based on STCs and interleaved sub-lattices to minimize the overall embedding distortion. Experimental results show that, satisfactory levels of coding performance can be achieved with adequate payloads. In the near future, the MIRO scheme would be further optimized by testing on different distortion functions and embedding structures. Acknowledgments. This work was supported by the NSFC under U , U and U , and National Key Technology R&D Program under 2014BAH41B01, 2016YFB , 2016QY15Z2500 and 2016YFB References 1. Richardson, I.E.: H.264 and MPEG-4 Video Compression: Video Coding for Nextgeneration Multimedia. Wiley, Hoboken (2004) 2. Cao, H., Zhou, J.L., Yu, S.S.: An implement of fast hiding data into H.264 bitstream based on intra-prediction coding. In: MIPPR 2005 SAR and Multispectral Image Processing, pp I 60430I. International Society for Optics and Photonics (2005) 3. Hu, Y., Zhang, C.T., Su, Y.T.: Information hiding based on intra prediction modes for H.264/AVC. In: 2007 IEEE International Conference on Multimedia and Expo, pp IEEE (2007) 4. Yang, G.B., Li, J.J., He, Y.L., Kang, Z.W.: An information hiding algorithm based on intra-prediction modes and matrix coding for H.264/AVC video stream. AEU- Int. J. Electron. Commun. 65(4), (2011) 5. Liu, C., Chen, OT.-C.: Data hiding in inter and intra prediction modes of H.264/AVC. In: 2008 IEEE International Symposium on Circuits and Systems, ISCAS 2008, pp IEEE (2008) 6. Xu, D.W., Wang, R.D., Wang, J.C.: Prediction mode modulated data-hiding algorithm for H.264/AVC. J. Real-Time Image Proc. 7(4), (2012) 7. Kapotas, S.K., Skodras, A.N.: Real time data hiding by exploiting the ipcm macroblocks in H.264/AVC streams. J. Real-Time Image Proc. 4(1), (2009) 8. Bouchama, S., Hamami, L., Aliane, H.: H.264/AVC data hiding based on intra prediction modes for real-time applications. In: Proceedings of the World Congress on Engineering and Computer Science, vol. 1, pp (2012) 9. Kim, D.-W., Choi, Y.-G., Kim, H.-S., Yoo, J.-S., Choi, H.-J., Seo, Y.-H.: The problems in digital watermarking into intra-frames of H.264/AVC. Image Vis. Comput. 28(8), (2010) 10. Filler, T., Fridrich, J.: Gibbs construction in steganography. IEEE Trans. Inf. Forensics Secur. 5(4), (2010) 11. Filler, T., Judas, J., Fridrich, J.: Minimizing additive distortion in steganography using syndrome-trellis codes. IEEE Trans. Inf. Forensics Secur. 6(3), (2011)