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

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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
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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
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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
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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
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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
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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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