Reversible Information Hiding Techniques and Their Applications in Image Protection Advisor： Chin-Chen Chang Student： Thai-Son Nguyen Department of Computer Science and Information Engineering, FengChia University June 29, 2015 1 Outline Introduction Reversible Data Hiding Schemes in spatial domain Scheme 1: A Novel Reversible Data Hiding Scheme Based on Difference-Histogram Modification and Optimal EMD Algorithm Scheme 2: An Efficient Reversible Data Hiding Scheme Based on Adaptive Rhombus Prediction and Pixel Selection Reversible Data Hiding Schemes in compressed domain Scheme 3: Reversible Data Hiding for Indices Based on Histogram Analysis Scheme 4: Adaptive Lossless Data-Hiding and Compression Scheme for SMVQ Indices Using SOC Applications of reversible data hiding Scheme 5 Reversible Authentication Scheme for Digital Images with High-Quality Images Scheme 6: A Blind Reversible Robust Watermarking Scheme for Relational Databases Conclusions and future works 2 Introduction-Motivation Encryption: Meaningless Information Hiding: Hide the secret data into a cover data (meaningful). Irreversible data hiding Reversible data hiding Three domains: spatial domain, compression domain, frequency domain Basic requirements: visual quality, hiding capacity, reversibility, compression rate, robustness Cover data: images, videos, audios, written texts, database 3 Introduction-Research Objectives To propose two RDH schemes in spatial domain with the high embedding capacity while maintaining the good image quality. To provide two RDH schemes in compressed domain, to improve further embedding capacity, compression rate, as well as embedding efficiency. To apply RDH for image authentication with high accuracy of tamper detection and high quality. To develop a reversible watermarking for relational database to protect them from illegal copying and manipulation by malicious attackers. 4 Scheme 1: A Novel Reversible Data Hiding Scheme Based on Difference-Histogram Modification and Optimal EMD Algorithm 5 A Novel Reversible Data Hiding Scheme Based on Difference-Histogram Modification and Optimal EMD Algorithm • Embedding phase 6 A Novel Reversible Data Hiding Scheme Based on Difference-Histogram Modification and Optimal EMD Algorithm • Embedding phase - Generation of Optimal EMD Table Divide the secret data into into sequence S = {s1, s2,… , s|R|/3}, si is 3 bits Histogram of sequences S Sorted histogram of sequences S Embed three bits each time Minimum embedding distortion Optimal EMD table 7 A Novel Reversible Data Hiding Scheme Based on Difference-Histogram Modification and Optimal EMD Algorithm • Embedding phase –Block classification Compute complexity If NV < T, smooth block. Otherwise, complex block 8 A Novel Reversible Data Hiding Scheme Based on Difference-Histogram Modification and Optimal EMD Algorithm • Embedding phase – Embedding procedure 150 150 151 149 152 151 149 152 150 T= 15 NV = 10 0 -2 0 -3 152 1 0 0 2 Peak = 0 Secret data = 001 011 Original block Optimal EMD table 0 -3 0 149 149 150 -4 152 2 148 152 150 1 0 3 149 152 149 Stego block 9 A Novel Reversible Data Hiding Scheme Based on Difference-Histogram Modification and Optimal EMD Algorithm • Extracting phase 149 149 150 T = 15 0 -2 0 148 152 150 Peak = 0 -3 152 1 0 0 2 149 152 149 Stego block Optimal EMD 0 -3 0 -4 152 2 1 0 3 [Peak -1, Peak +1] 150 150 151 Secret data = 001 011 149 152 151 149 152 150 Original block 10 A Novel Reversible Data Hiding Scheme Based on Difference-Histogram Modification and Optimal EMD Algorithm •Experimental results Lena Boat [8] X. Li, B. Yang, and T. Zeng, “Efficient reversible watermarking based on adaptive prediction-error expansion and pixel selection,” IEEE Trans. Image Process., vol. 20, no. 12, pp. 3524-3533, Dec. 2011. [12] X. Li, B. Li, B. Yang, and T. Zeng, “General framework to histogram-shifting-based reversible data hiding,” IEEE Trans. on Image Process., vol. 22, no. 6, pp. 2181-2191, Jun. 2013. [19] W. Hong, “Adaptive reversible data hiding method based on error energy control and histogram shifting,” Opt. Commun., vol. 285, no. 2, pp. 101-108, 2012. [20] V. Sachnev, H. J. Kim, J. Nam, S. Suresh, and Y.Q. Shi, “Reversible watermarking algorithm using sorting and prediction,” IEEE Trans. Circuits Syst. Video Technol., vol. 19, no. 7, pp. 989-999, Jul. 2009. 11 A Novel Reversible Data Hiding Scheme Based on Difference-Histogram Modification and Optimal EMD Algorithm •Experimental results Baboon Peppers 12 A Novel Reversible Data Hiding Scheme Based on Difference-Histogram Modification and Optimal EMD Algorithm •Experimental results Table 2.1 Comparison of PSNR (dB) between the proposed scheme four previous schemes [8, 12, 19, 20] for EC of 10,000 bits Images Sachnev et al. [20] Li et al. [8] Hong et al. [19] Li et al. [12] Proposed Lena 58.18 58.12 58.64 59.37 59.37 F16 60.38 60.74 61.72 62.65 61.53 Baboon 54.15 54.21 53.29 54.41 55.35 Peppers 55.55 56.06 56.02 56.89 58.71 Sailboat 58.15 58.12 57.29 58.27 58.26 Boat 56.15 55.57 56.55 57.16 58.61 Average 57.09 57.14 57.25 58.13 58.64 13 A Novel Reversible Data Hiding Scheme Based on Difference-Histogram Modification and Optimal EMD Algorithm • Summary An optimal EMD table is generated for RDH Reversibility High image quality and high embedding capacity 14 Scheme 2: An Efficient RDH Scheme Based on Adaptive Rhombus Prediction and Pixel Selection 15 An Efficient RDH Scheme Based on Adaptive Rhombus Prediction and Pixel Selection •Embedding phase Rhombus prediction 16 An Efficient RDH Scheme Based on Adaptive Rhombus Prediction and Pixel Selection •Embedding phase- Pixel selection Compute local complexity If LVx < TH, select it for embedding data. Then, calculate predicted value 17 An Efficient RDH Scheme Based on Adaptive Rhombus Prediction and Pixel Selection •Embedding phase 250 252 250 197 190 LV X 1 TH 252 252 253 223 185 PX round [( 252 252 ) / 2 ] 252 253 252 253 254 180 e PX PX 252 252 0 252 252 252 253 255 Skip unchanged 252 252 250 253 170 LV X 125 TH TH = 5 Prediction errors e = 0 1 0 -1 18 An Efficient RDH Scheme Based on Adaptive Rhombus Prediction and Pixel Selection •Embedding phase Peak P Zero Z e= 0 , 1, 0 , 1 e 1, if e ( P , Z ) e e w , if e P e , Otherwise P = 0, Z = 2 W=01 e= 0 2 1 1 19 An Efficient RDH Scheme Based on Adaptive Rhombus Prediction and Pixel Selection •Embedding phase e= 250 252 250 197 190 252 252 253 223 185 0 , 2 , 1, 1 P ( i , j ) P ( i , j ) e ( i , j ) 252 0 252 253 252 253 254 254 180 P ( i , j ) P ( i , j ) e ( i , j ) 252 2 254 252 253 252 252 253 255 P ( i , j ) P ( i , j ) e ( i , j ) 252 1 253 252 252 250 253 170 Stego image P ( i , j ) P ( i , j ) e ( i , j ) 254 1 253 20 An Efficient RDH Scheme Based on Adaptive Rhombus Prediction and Pixel Selection •Extracting phase 250 252 250 197 190 252 252 253 223 185 253 252 254 254 180 e 1, if e ( P , Z ] e e , Otherwise e 0 , 1, 0 , 1 252 253 252 253 255 252 252 250 253 170 250 252 250 197 190 e ( i , j ) P ( i , j ) P ( i , j ) 252 252 253 223 185 e 0 , 2 , 1, 1 P = 0, Z = 2 253 252 254 254 180 0 , if e P w 1, if e P 1 252 252 252 253 255 W = 01 252 252 250 253 170 Original image 21 An Efficient RDH Scheme Based on Adaptive Rhombus Prediction and Pixel Selection Optimal pair of peak and zero points Embedding capacity L Two possible cases: 1. F(Pl) L, (Pl, Zl) is the first candidate 2. F(Pr) L, (Pr, Zr) is the second candidate 3. Optimal one is selected with the smaller embedding distortion 22 An Efficient RDH Scheme Based on Adaptive Rhombus Prediction and Pixel Selection Experimental results 23 An Efficient RDH Scheme Based on Adaptive Rhombus Prediction and Pixel Selection Lena Baboon Airplane Peppers 24 An Efficient RDH Scheme Based on Adaptive Rhombus Prediction and Pixel Selection Sailboat Boat [12] X. Li, B. Li, B. Yang, and T. Zeng, “General framework to histogram-shifting-based reversible data hiding,” IEEE Trans. on Image Process., vol. 22, no. 6, pp. 2181-2191, Jun. 2013. [13] J. Wang, J. Ni, and Y. Hu, “An efficient reversible data hiding scheme using prediction and optimal side information selection,” J. Vis. Commun. Image Represent., vol. 25, pp. 1425-1431, 2014. [20] V. Sachnev, H. J. Kim, J. Nam, S. Suresh, and Y.Q. Shi, “Reversible watermarking algorithm using sorting and prediction,” IEEE Trans. Circuits Syst. Video Technol., vol. 19, no. 7, pp. 989-999, Jul. 2009. [21] L. Luo, Z. Chen, M. Chen, X. Zeng, and Z. Xiong “Reversible image watermarking using interpolation technique,” IEEE Trans. Inf. Forens. 25 Secur., vol. 5, no. 1, pp. 187-193, 2010. An Efficient RDH Scheme Based on Adaptive Rhombus Prediction and Pixel Selection Summary Adaptive rhombus prediction and pixel selection techniques are used for RDH Higher performance in terms of image quality and embedding capacity 26 Scheme 3: Reversible Data Hiding for Indices Based on Histogram Analysis 27 Reversible Data Hiding for Indices Based on Histogram Analysis Encoding method Frequency of indices Tiffany Goldhill Indices [0,7] 0.00% 6.24% VQ only Indices [8,255] 100.00% 93.76% Indices [0,7] 87.70% 59.72% VQ and SMVQ Indices [8,255] 12.30% 40.28% Peppers 16.84% 83.16% 77.21% 22.79% 28 Reversible Data Hiding for Indices Based on Histogram Analysis Histogram analysis The number of zero frequency is U = 9 log( U 1) 3 n 0 Integer log 2 The largest mapping bits n0 U C 1 ( 2 1) C 2 ( 2 1) ... C n 0 ( 2 1 Sorted histogram mapping 2 n0 1) C ( 2 1) i i i 1 func 1 : 9 6 ( 2 1) 1 ( 2 1) 0 ( 2 1) 1 where C 1 6 , 2 C 2 1, 3 C3 0 [2 0 1], [0 3 0], [3 2 0] 0], and [6 1 0] Achieve higher embedding capacity Low compression rate as traditional VQ 29 Reversible Data Hiding for Indices Based on Histogram Analysis Embedding phase S = 10 00 11 01 10 Transformed index table IT 8 1 1 0 3 9 7 1 2 3 6 4 1 8 2 5 Stego index table 30 Reversible Data Hiding for Indices Based on Histogram Analysis 0.80 Experimental results Compression rate 0.70 0.60 Proposed 0.50 Yang & Lin Wang & Lu Lu et al. 0.40 VQ Lee et al. 0.30 Chang et al. 0.20 0.10 0.00 Lena Peppers Baboon Boat Tiffany F16 Goldhill Couple Sailboat Zelda Barbara Bridge Average Test images Figure 4.11 Compression rate results of our proposed scheme and some previous schemes 31 Reversible Data Hiding for Indices Based on Histogram Analysis Experimental results 4.50 4.00 Embedding rate 3.50 3.00 Proposed Yang & Lin 2.50 Wang & Lu Lu et al. 2.00 Lee et al. Chang et al. 1.50 1.00 0.50 0.00 Lena Peppers Baboon Boat Tiffany F16 Goldhill Couple Sailboat Zelda Barbara Bridge Average Test images Figure 4.12 Embedding rate (ER) results of our proposed scheme and some previous schemes 32 Reversible Data Hiding for Indices Based on Histogram Analysis Summary Preserve image quality and compression rate the same as those of traditional VQ. Improve embedding rate of previous schemes further [46] Z. M. Lu, J. X Wang, and B. B. Liu, “An improved lossless data hiding scheme based on image VQ-index residual value coding,” Journal of Systems and Software, vol. 82, pp. 1016-1024, 2009. [47] C. H. Yang and Y. C. Lin, “Reversible data hiding of a VQ index table based on referred counts,” J. Vis. Commun. Image Represent., vol. 20, no. 6, pp. 399-407, Aug. 2009. [48] J. X. Wang and Z. M. Lu, “A path optional lossless data hiding scheme based on VQ joint neighboring coding”, Information Sciences, vol. 179, pp. 3332-3348, 2009. [49] C. F. Lee, H. L. Chen, and S. H. Lai, “An adaptive data hiding scheme with high embedding capacity and visual image quality based on SMVQ prediction through classification codebooks,” Image and Vision Computing, vol. 28, no. 8, pp. 1293-1302, 2010. [50]C. C. Chang, T. S. Nguyen, and C. C. Lin, “A novel VQ-based reversible data hiding scheme by using hybrid encoding strategies,” Journal of Systems and Software, vol. 86, pp. 389-402, 2013. 33 Scheme 4: Adaptive Lossless DataHiding and Compression Scheme for SMVQ Indices Using SOC 34 Adaptive Lossless Data-Hiding and Compression Scheme for SMVQ Indices Using SOC VQ and SOC 3500 Number of indices 3000 2500 2000 1500 1000 500 0 1 51 101 151 201 251 Index value Figure 5.2 Distribution of indices by using VQ compression and SOC algorithm Number of indices SMVQ and SOC 4500 4000 3500 3000 2500 2000 1500 1000 500 0 1 51 101 151 201 251 Index value Figure 5.3 Distribution of indices by using SMVQ compression and SOC algorithm 35 Adaptive Lossless Data-Hiding and Compression Scheme for SMVQ Indices Using SOC Figure 5.5 The main processes of the proposed embedding algorithm 36 Adaptive Lossless Data-Hiding and Compression Scheme for SMVQ Indices Using SOC Table 5.3 Encoding rule of the proposed scheme Encoding rule Cases Compression code Case 1 00 Case 2 01|| SOC-2bit Case 3 10||OIV of P 11||indicatori||0||log2(thr) bits Case 4 of |d| 11||indicatori||1||log2(thr) bits Case 5 of |d| Under-hiding m1 = 5 bits m2 = 3 bits 00|| m1 secret bits 01||SOC-2bit || m2 secret bits - Normal-hiding m1 = 6 bits m2 = 4 bits 00|| m1 secret bits 00||SOC-2bit || m2 secret bits - Over-hiding m1 = 7 bits m2 = 5 bits 00|| m1 secret bits 00||SOC-2bit || m2 secret bits - - - - - - - 37 Adaptive Lossless Data-Hiding and Compression Scheme for SMVQ Indices Using SOC 4 11 Case 3 Case 4 0 4 Case 1 Case 2 SMVQ index table Secret message 101110 1010 Threshold thr = 8, m1 = 6, m2 = 4 Code steam CS 10||00000100 11||00||0||111 00||101110 01||01||1010 38 Adaptive Lossless Data-Hiding and Compression Scheme for SMVQ Indices Using SOC Images Lena Airplane Tiffany Peppers Sailboat Boat Average Parameters EC CR EF EC CR EF EC CR EF EC CR EF EC CR EF EC CR EF EC CR EF Under-hiding 43,463 0.46 36.40% 60,488 0.45 51.15% 71,707 0.44 62.19% 43871 0.46 36.57% 42042 0.46 34.63% 44886 0.46 37.51% 51,076 0.45 43.08% Qin et al. [64] 10,292 0.40 9.72% 11,182 0.39 10.91% 11,566 0.39 11.46% 11,295 0.39 11.08% 7,247 0.45 6.09% 9,301 0.42 8.41% 10,147 0.41 9.61% Pan et al.[65] 16,384 0.52 12.02% 16,384 0.51 12.25% 16,384 0.49 12.76% 16,384 0.54 11.57% 16,384 0.53 11.79% 16,384 0.51 12.25% 16,384 0.52 12.10% 39 Adaptive Lossless Data-Hiding and Compression Scheme for SMVQ Indices Using SOC Images Lena Airplane Tiffany Peppers Sailboat Boat Average Parameters EC CR EF EC CR EF EC CR EF EC CR EF EC CR EF EC CR EF EC CR EF Normal-hiding Over-hiding Lee et al.[63] Wang et al.[66] 56,322 69,181 46,962 46,694 0.50 0.55 0.52 0.49 42.59% 47.67% 34.45% 36.35% 74,064 87,640 57,933 59,473 0.50 0.55 0.52 0.53 56.18% 60.28% 42.50% 42.81% 87,522 103,337 72,177 74,875 0.50 0.56 0.51 0.56 66.75% 70.33% 53.67% 51.00% 56470 69,069 45516 49,480 0.51 0.55 0.52 0.50 42.60% 47.58% 33.33% 37.75% 53,396 64,750 44046 49,152 0.51 0.55 0.52 0.50 40.22% 44.93% 32.07% 37.50% 57,578 70,270 39042 48,634 0.50 0.55 0.52 0.51 43.51% 48.45% 28.70% 36.38% 64,225 77,375 50,946 54,718 0.50 0.55 0.52 0.52 48.64% 53.21% 37.45% 40.30% 40 Adaptive Lossless Data-Hiding and Compression Scheme for SMVQ Indices Using SOC Summary High EC and high EF while guaranteeing a low CR. Further improve the performance of four previous schemes [63-66] [63] J. D. Lee, Y. H. Chiou, and J. M. Guo, “Lossless data hiding for VQ indices based on neighboring correlation,” Information Sciences, vol. 221, pp. 419-438, Dec. 2013. [64] C. Qin, C. C. Chang, Y. P. Ping, “A novel joint data hiding and compression scheme based on SMVQ and image inpainting,” IEEE Trans. Image Process., vol. 23, no. 3, pp. 969-978, Mar. 2014. [65]Z. B. Pan, X. X. Ma, X. M. Deng, S. Hu, “Low bit-rate information hiding method based on search-order-coding technique,” Journal of Systems and Software, vol. 86, pp. 2863-2869, 2013. [66] L. F. Wang, Z. B. Pan, X. X. Ma, S. Hu, “A novel high-performance reversible data hiding scheme using SMVQ and improved locally adaptive coding method,” J. Vis. Commun. Image Represent., vol. 25, pp. 454-465, 2013. 41 Scheme 5: A Reversible Authentication Scheme for Digital Images with High-Quality Images 42 A Reversible Authentication Scheme for Digital Images with High-Quality Images Figure 6.1 Framework of the proposed authentication scheme 43 A Reversible Authentication Scheme for Digital Images with High-Quality Images Figure 6.2 Example of an image block and its satellite reference pixels 44 A Reversible Authentication Scheme for Digital Images with High-Quality Images 25 24 25 25 25 26 23 22 24 dL = L- C = 0 dL’ = 2 x 0 + 1 = 1 dR = R - C = 1 dR’ = 2 x 1 + 0 = 2 Original block T* = 2 W=10 25 24 25 26 25 27 23 22 24 Stego block 45 A Reversible Authentication Scheme for Digital Images with High-Quality Images 58 Lena 56 Boat PSNR Airplane 54 Girl 52 Goldhill Peppers 50 48 46 44 42 40 0 1 2 3 4 5 T* Figure 6.6 Image quality of the embedded images of the proposed scheme 46 A Reversible Authentication Scheme for Digital Images with High-Quality Images (a) T* = 0 (b) T* = 1 (d) T* = 2 (e) T* = 3 Figure 6.9 Tampered images “Lena” of the proposed scheme with various values of T* 47 A Reversible Authentication Scheme for Digital Images with High-Quality Images (a) Refined detected image with T* = 0, NC = 0.9192 (c) Refined detected image with T* = 2, NC = 0.9236 (b) Refined detected image with T* = 1, NC = 0.9220 (d) Refined detected image with T* = 3, NC = 0.9428 48 A Reversible Authentication Scheme for Digital Images with High-Quality Images Table 6.5 Comparison of the proposed scheme and Lo and Hu’s scheme Authentication code Schemes Block size Clear tamper Average PSNRs Average NC bits per block area Lo and Hu 4×4 2.76 51.48 dB 0.9106 Yes Proposed 3×3 1.35 51.72 dB 0.9429 Yes [86] C. C. Lo, Y. C. Hu, “A novel reversible image authentication scheme for digital images,” Signal Process., vol. 98, pp. 174-185, 2014. 49 A Reversible Authentication Scheme for Digital Images with High-Quality Images Summary Obtain high accuracy of tamper detection and preserve high quality of the stego images. Achieve reversibility. 50 Scheme 6: A Blind Reversible Robust Watermarking Scheme for Relational Databases 51 A Blind Reversible Robust Watermarking Scheme for Relational Databases Embed Watermark Relational database ReversibleIrreversible and more robustness 52 A Blind Reversible Robust Watermarking Scheme for Relational Databases 53 A Blind Reversible Robust Watermarking Scheme for Relational Databases ID A1 A2 A3 A4 PK1 295 52 75 48 PK8 256 75 94 25 PK13 126 451 451 455 PK17 55 15 11 512 PK23 75 126 452 964 PK30 94 58 254 54 Database Assume that selected attribute: ATT(PK1) = 2 ATT(PK8) = 1 ATT(PK13) = 4 ATT(PK17) = 1 ATT(PK23) = 3 ATT(PK30) = 3 Get two last digits of each selected attributes Seq = 52, 52, 54, 55, 55, 56 Mid = 54 Diff_Seq [i] =Seq [i] - mid Diff_Seq = -2, -2, 0, 1, 1, 2 54 A Blind Reversible Robust Watermarking Scheme for Relational Databases 3 Diff _Seq= -2, -2, 0, 1, 1, 2 PP1 2 PP2 1 ZP1 ZP2 0 -3 -2 -1 0 1 2 3 2 3 3 PP1 2 Diff _Seq= -2, -2, 0, 1, 1, 3 PP2 1 0 -3 -2 -1 0 1 Histogram after shifting 55 A Blind Reversible Robust Watermarking Scheme for Relational Databases Diff _Seq= -2, -2, 0, 1, 1, 3 PP1 PP2 Watermark b = 1 0 1 0 Hide ‘1’ in – 2 – 2 – b = – 2 – 1 = – 3 Hide ‘0’ in – 2 – 2 – b = – 2 – 0 = – 2 Hide ‘1’ in 1 1 + b = 1 + 1 = 2 Hide ‘0’ in 1 1 + b = 1 + 0 = 1 Diff _Seq becomes -3, -2, 0, 2, 1, 3 Histogram after shifting ID A1 A2 A3 A4 PK1 295 51 75 48 PK8 257 75 94 25 PK13 126 451 451 456 PK17 55 15 11 512 PK23 75 126 452 964 PK30 94 58 254 54 56 A Blind Reversible Robust Watermarking Scheme for Relational Databases Experimental results 110% 100% 90% Watermark match(%) 80% 70% 60% 50% 40% Proposed scheme with g= 6, and without MVT 30% Proposed scheme with g= 6, and with MVT 20% Shehab et al.'s scheme 10% Farfoura et al.'s scheme 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Altered tuples(%) Figure 7.7 Comparison of the results for resilience to an alteration attack by the two proposed schemes and two other schemes 57 A Blind Reversible Robust Watermarking Scheme for Relational Databases Experimental results 110% 100% 90% Watermark match(%) 80% 70% 60% 50% 40% Proposed scheme with g= 6, and without MVT 30% Proposed scheme with g= 6, and with MVT 20% Shehab et al.'s scheme 10% Farfoura et al.'s scheme 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Deleted tuples(%) Figure 7.8 Comparison of the results for the resilience to the detection attack of the two proposed schemes and two other schemes 58 A Blind Reversible Robust Watermarking Scheme for Relational Databases Summary Achieves reversibility. Resilient to various attacks. [89] M. Shehab, E. Bertino, and A. Ghafoor, “Watermarking relational databases using optimization-based techniques,” IEEE Trans. Knowledge Data Engineer., vol. 20, no. 1, pp. 116, 129, Jan. 2008. [92] M. E. Farfoura, S. J. Horng, J. L. Lai, R. S. Run, R. J. Chen, and M. K. Khan, “A blind reversible method for watermarking relational databases based on a time-stamping,” Expert Systems with Applications, vol. 39, pp. 3185-3196, 2012. 59 Conclusions Six RDH techniques have been proposed in this study with high performances: Reversibility. Good image quality. Higher embedding capacity. Lower compression rate. High accuracy of tampered detection. More robustness. 60 Future works For the RDH schemes of Chapter 2 and Chapter 3, only one bit is embedded into each pixel. Therefore, we try to improve embedding capacity as well as image quality (i.e., larger than 1 bit per pixel and greater than 60 dB). Enhance the performance of my proposed schemes in Chapters 4 and 5, i.e., higher embedding rate (up to 6 bits per index) and lower compression rate (less than 0.4 bit per pixel) while guaranteeing good image quality of reconstructed image (PSNRs > 30dB) . Improve the Scheme 6 in Chapter 7 to achieve more security against some malicious attacks in relational database (e.g. deletion, sorting, modification, addition attacks) Develop RDH schemes in the frequency domain by using Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) to achieve high robustness. Develop reversible data hiding techniques for encrypted images and high dynamic range (HDR) images. Address data hiding algorithms for 3D images, stereo images, and videos. 61 Publication list International Journal Papers: 1. C. C., Chang, T. S. Nguyen, and C. C. Lin, “A reversible data hiding scheme for VQ indices using locally adaptive coding,” Journal of Visual Communication and Image Representation (JVCI), vol. 22, no. 7, pp. 664672, Oct. 2011. (SCI) 2. W. X. Tian, C. C. Chang, T. S. Nguyen, and M. C. Li, “Reversible data hiding for high quality image exploiting interpolation and direction order mechanism,” Digital Signal Processing, vol. 23, no. 2, pp. 569-577, Mar. 2013. (SCI) 3. C. C., Chang, T. S. Nguyen, and C. C. Lin, “A novel VQ-based reversible data hiding scheme by using hybrid encoding strategies,” Journal of Systems and Software, (JSS) vol. 86, no. 2, pp. 389-402, Feb. 2013. (SCI) 4. C. C., Chang, T. S. Nguyen, and C. C. Lin, “Distortion-free data hiding for high dynamic range images,” Journal of Electronic Science and Technology, (JEST) vol. 11, no. 1, pp. 20-26, Mar. 2013. (EI) 5. C. C., Chang, T. S. Nguyen, and C. C. Lin, “Reversible image hiding for high image quality based on histogram shifting and local complexity,” International Journal of Network and Security (IJNS), vol. 16, no. 3, pp. 201-213, May 2014 . (EI, Scopus) 6. C. C., Chang, T. S. Nguyen, and C. C. Lin, “A blind reversible robust watermarking scheme for relational databases,” Scientific World Journal (SWJ), volume 2013. (SCI) 7. C. C., Chang, T. S. Nguyen, and C. C. Lin, “A novel compression scheme based on SMVQ and Huffman coding,” International Journal of Innovative Computing, Information and Control, vol. 10, no. 3, June 2014. (EI, Scopus) 8. C. C., Chang, T. S. Nguyen, and C. C. Lin, “A reversible data hiding scheme for VQ indices based on absolute difference trees,” KSII Transactions on Internet and Information Systems, vol. 8, no. 7, Jul. 2014. (SCI) 9. C. C., Chang, T. S. Nguyen, and C. C. Lin, “Reversible data embedding for indices based on histogram analysis,” Journal of Visual Communication and Image Representation (JVCI), vol. 25, no. 7, pp. 1704-1716, 62 Oct. 2014. (SCI, EI) Publication list 10. T. S. Nguyen, C. C. Chang, and T. F. Chung, “A tamper-detection scheme for BTC-compressed images with high-quality images,” KSII Transactions on Internet and Information Systems, vol. 8, no. 6, Jun. 2014. (SCI) 11. T. S. Nguyen, C. C. Chang, and M. C. Lin, “Adaptive lossless data-hiding and compression scheme for SMVQ indices using SOC,” Smart Computing Review, vol. 4, no. 3, Jun. 2014. 12. W. L. Lyu, C. C. Chang, T. S. Nguyen, and C. C. Lin, “Image watermarking scheme in areas of interest using scale-invariant feature transform,” KSII Transactions on Internet and Information Systems, vol. 8, no. 10, 2014. (SCI) 13. C. C., Chang, T. S. Nguyen, and C. C. Lin, “A new distortion-free data embedding scheme for high dynamic images,” Multimedia Tools and Applications, Available on 28/9/2014 (SCI) 14. C. C. Chang and T. S. Nguyen, “A reversible data hiding scheme for SMVQ indices,” Informatica, vol. 25, no. 4, pp. 523–540, 2014. (SCI) 15. C. C., Chang, T. S. Nguyen, and C. C. Lin, “A reversible compression code hiding using SOC and SMVQ indices,” Information Sciences, vol. 300, pp. 85-99, 2015. (SCI) International Conference Papers 16. C. C. Chang, Y. J. Liu, and T. S. Nguyen, “A novel turtle shell based scheme for data hiding,” Proceedings of the 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP14),Kitakyushu, Japan (EI) (Best paper award). 17. C. C., Chang, T. S. Nguyen, and C. C. Lin, “A virtual primary key for reversible watermarking textual relational databases,” Proceedings of The International Computer Symposium 2014, Dec., 2014, Taichung, Taiwan, pp. 756-769. 18. C. C. Chang, Y. J. Liu, and T. S. Nguyen, “Hiding secret information in block truncation code using dynamic programming strategy,” 6th International Conference on Graphic and Image Processing (ICGIP 2014), Beijing, China, 2014/10/24-26. (Best paper award). 19. C. C., Chang, T. S. Nguyen, and C. C. Lin, “A blind robust reversible watermark scheme for textual relational databases with virtual primary key,” 13th International Workshop on Digital-Forensics and 63 Watermarking (IWDW 2014), October 1-4, 2014, Taipei, Taiwan. Publication list Submitted Papers 20. C. C., Chang, T. S. Nguyen, and C. C. Lin, “New compression algorithms based on SOC and SMVQ,” submitted to Informatica (Submitted 2014/12/25) (SCI / EI, Impact Factor: 0.901) (Reviewing). 21. C. C. Chang and T. S. Nguyen, “A reversible data hiding scheme based on the Sudoku technique,” submitted to Displays (Submitted: 2013/01/27) (SCI / EI, Impact Factor: 1.390) (Reviewing). 22. C. C. Chang and T. S. Nguyen, “A reversible data hiding scheme for image interpolation based on reference matrix,” submitted to Journal of Imaging Science and Technology (Submitted: 2013/10/17). (SCI / EI, Impact Factor: 1.390) (Reviewing). 23. C. C., Chang, T. S. Nguyen, and C. C. Lin, “A blind reversible robust watermarking scheme for categorical relational databases,” submitted to Computers & Security (Submitted: 2015/04/15) (SCI , Impact Factor: 1.488) 24. T. S. Nguyen, C. C. Chang, W. C. Chang, C. C. and Lin, “High capacity reversible data hiding for BTC images,” submitted to ACM Transactions on Multimedia Computing, Communication and Applications (Submitted: 2015/3/24). (SCI, Impact Factor: 0.48) 25. C. C. Chang, T. S. Nguyen, M. C. Lin, and C. C. Lin, “A novel data-hiding and compression scheme based on block classification of SMVQ indices,” submitted to Digital Signal Processing (Submitted: 2014/07). (SCI, Impact Factor: 2.018) (Revision) 26. T. S. Nguyen, C. C. Chang, and T. H. Shih, “A high-quality reversible image authentication based on adaptive PEE for digital images,” submitted to KSII Transactions on Internet and Information Systems (Submitted: 2015/04/09). (SCI, Impact Factor: 0.56) 27. T. S. Nguyen, C. C. Chang, and T. H. Shih, “A reversible authentication scheme for digital images with high-quality images,” submitted to Multimedia Tools and Applications (Submitted: 2015/01/20). (SCI, Impact Factor: 1.058) 28. Y. J. Liu, C. C. Chang, and T. S. Nguyen, “A high capacity data hiding scheme based on turtle shell,” submitted to IET Image Processing (Submitted: 2014/12/21). (SCI, Impact Factor: 0.676) 64 Publication list 29. T. S. Nguyen, C. C. Chang, and H. S. Hsueh, “High capacity data hiding for binary image based on block classification,” submitted to Multimedia Tools and Applications (Submitted: 2014/12/28). (SCI, Impact Factor: 1.058) 30. H. L. Wu, C. C. Chang, and T. S. Nguyen, “Reversible data hiding using pixel order exchange,” submitted to Journal of Visual Languages & Computing (Submitted: 2015/05/20). (SCI, Impact Factor: 0.8) 31. T. S. Nguyen, C. C. Chang, and N. T. Huynh, “A novel reversible data hiding scheme based on differencehistogram modification and optimal EMD algorithm,” submitted to Journal of Visual Communication and Image Representation (JVCI) (Submitted: 2015/1/30). (SCI, Impact Factor: 1.430) 32. T. S. Nguyen, C. C. Chang, and X. Q. Yang, “High-quality semi-fragile watermarking for image authentication and tamper detection,” submitted to Computers & Security (Submitted: 2015/2). (SCI, Impact Factor: 1.488) 33. T. S. Nguyen, C. C. Chang, and H. L. Wu, “Adaptive image sharing scheme based on quadri-directionalsearch-strategy with meaningful shadows,” submitted to Multimedia Tools and Applications (SCI, Impact Factor: 1.058) 34. C. C. Chang, Nguyen, T. S., and C. C. Lin, “A blind, reversible, robust watermarking scheme for textual and numerical relational databases,” submitted to Systems, Man, and Cybernetics: Systems, IEEE Transactions on (Submitted: 2015/4/15) 35. T. S. Nguyen, C. C. Chang, and W. C. Chang, “High capacity reversible data hiding scheme for encrypted images,” submitted to Signal Processing: Image Communication (Submitted: 2015/04/13). (SCI, Impact Factor: 1.28) 36. T. S. Nguyen, C. C. Chang, and C. C. Lin, “High capacity reversible data hiding scheme based on AMBTC for encrypted images,” submitted to IEEE Trans. on Cybernetics (Submitted: 2015/4/20). 37. T. S. Nguyen, C. C. Chang, and W. C. Chang, “An efficient reversible data hiding scheme based on rhombus prediction and pixel selection,” submitted to Information Sciences (Submitted: 2015/05/14). (SCI, 65 Impact Factor: 3.969) Publication list 38. T. S. Nguyen, C. C. Chang, and H. S. Hsueh, “High-quality Data Hiding Algorithm for H.246/AVC Video Stream without Intra-Frame Distortion Drift,” Neurocomputing (Submitted: 2015/05/19). (SCI) 39. T. S. Nguyen, C. C. Chang, and T. H. Shih, “Effective reversible image authentication based on rhombus prediction and local complexity,” submitted to Journal of Visual Languages & Computing (Submitted: 2015/05/26). (SCI) 40. T. S. Nguyen, C. C. Chang, and Y. Q. Yang, “Fragile watermarking for image authentication based on DWT-SVD-DCT features with High-quality,” submitted to Signal Processing (Submitted: 2015/06/09). (SCI) 66 Thanks for your listening ! 67

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