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to embed a message using watermarking in the encryption domain. This protocol ... and homomorphic encryption method for buyer-seller watermarking protocol.
Journal of Korea Multimedia Society Vol. 17, No. 12, December 2014(pp. 1402-1411) http://dx.doi.org/10.9717/kmms.2014.17.12.1402

DCT and Homomorphic Encryption based Watermarking Scheme in Buyer-seller Watermarking Protocol Teak-Young Seong†, Ki-Chang Kwon††, Suk-Hwan Lee†††, Kwang-Seok Moon††††, Ki-Ryong Kwon†††††

ABSTRACT Buyer-seller watermarking protocol is defined as the practice of imperceptible altering a digital content to embed a message using watermarking in the encryption domain. This protocol is acknowledged as one kind of copyright protection techniques in electronic commerce. Buyer-seller watermarking protocol is fundamentally based on public-key cryptosystem that is operating using the algebraic property of an integer. However, in general usage, digital contents which are handled in watermarking scheme mostly exist as real numbers in frequency domain through DCT, DFT, DWT, etc. Therefore, in order to use the watermarking scheme in a cryptographic protocol, digital contents that exist as real number must be transformed into integer type through preprocessing beforehand. In this paper, we presented a new watermarking scheme in an encrypted domain in an image that is based on the block-DCT framework and homomorphic encryption method for buyer-seller watermarking protocol. We applied integral-processing in order to modify the decimal layer. And we designed a direction-adaptive watermarking scheme by analyzing distribution property of the frequency coefficients in a block using JND threshold. From the experimental results, the proposed scheme was confirmed to have a good robustness and invisibility. Key words: Intellectual Property, Buyer-seller Watermarking Protocol, Security, Cryptographic Protocol, Watermarking.

Advancement of computing and the networking technology, which enables high-speed calculation and ability to connect each person via internet have been growing very rapidly over the past decade. Like a two-sided coins, while this advancement provided availability for users to perform various operations like composing, editing, transforming, duplicating, and fast distribution of numerous mul-

timedia contents. It also permits malicious users to do unauthorized duplication and redistribution easily. Therefore, this technology is considered bring detrimental effect upon the protection of intellectual property right. There are various kinds of techniques to solve these problems. Among them digital watermarking techniques are considered one of the most promising solutions. The idea of digital watermarking techniques is to embed tiny signals or message in

※ Corresponding Author : Ki-Ryong Kwon, Address:

†††††Dept. of IT Cooperative System, Gyeongbuk Provincial

1. INTRODUCTION

(608-738) (599-1) Daeyeon-3dong, Namgu, Busan, Korea, TEL : +82-51-629-6250, FAX : +82-51-629-6264, E-mail : [email protected] Receipt date : May 16, 2014, Revision date : Oct. 18, 2014 Approval date : Oct. 22, 2014 †Interdisciplinary Program of Information Security, Pukyong National University (E-mail : [email protected])

College (E-mail : [email protected])

†††††Dept. of Information Security, Tongmyong Univer-

sity (E-mail : [email protected])

†††††Dept. of Electronics Engineering, Pukyong National

University (E-mail : [email protected])

†††††Interdisciplinary Program of Information Security,

Pukyong National University

※ This work was supported by a Research Grant of Pukyong National University (2014Year)

DCT and Homomorphic Encryption based Watermarking Scheme in Buyer-seller Watermarking Protocol

certain digital contents in order to keep ownership information. So, at discovery of a pirate copy sometime later, the owner can assert the lawful ownership of the original digital contents through the detecting process of watermarks [1-3]. In several company which utilized watermarking techniques, it has been studied cryptographic protocols that can offer a reliable business transaction process to all of the parties in electronic commerce, and buyer-seller watermarking protocol is one of those protocols. Buyer-seller watermarking protocol combines a cryptographic protocol with a digital watermarking scheme. This method will provide clarification of copyright responsibility at discovery of a pirate copy by some illegal users. In the previous study, symmetric protocols were proposed. But, unfortunately, they were designed for both a buyer and a seller can access watermarked contents. Accordingly, when it is found an illegal replica, they have the customer's right problem which is not able to clarify responsibility issue [4]. Therefore, asymmetric protocols which were proposed after that time, is designed as a buyer can be only able to access watermarked contents while doing the transaction. In this way, they solved the problem of clarifying the responsible person at discovery of a pirate copy in symmetric protocols [5-7]. However, these protocols also have another problem. Once the seller discovers a pirated copy, it is possible for her to transplant the watermark embedded in the illegal copy into another copy of a digital content, provided both copies are sold to the same buyer. This problem is called unbinding problem. Chin-Laung Lei et al.[8] proposed a watermarking protocol that solves unbinding problem by designed buyer-seller watermarking protocol based on anonymous certificates and one time public-key cryptosystem for seller not to use the watermark embedded in the illegal copy, in the event of discovery. In watermarking techniques for digital images as one of the representative digital contents, it is

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desirable to embed watermarks in the frequency components based on DFT, DCT, DWT and etc. for robustness, invisibility and capacity purpose. In the buyer-seller watermarking protocol, public-key cryptosystem is operated in the basis of the algebraic property of an integer, but generally, images which are handled in most watermarking schemes exist as real number in frequency domain. These data type differences produce some problems in combining watermarking techniques with cryptographic protocols directly. But, previous researchers are mostly had not considered on how to implement watermarking scheme in an encrypted domain. Therefore, in this paper, the author presented a study of a new watermarking scheme in an encrypted domain in an image that is based on the block-DCT framework and homomorphic encryption method for buyer-seller watermarking protocol. Our study started with investigation about how to divide frequency coefficients exists as real number into integer and decimal layer in order to implement watermarking scheme in a public-key cryptosystem. We applied integralprocessing in order to modify the decimal layer. Also, for robustness and invisibility requirements in watermarking scheme, we designed a direction-adaptive watermarking scheme based on locally edge-properties of each block in an image by analyzing distribution property of the frequency coefficients in a block using JND threshold. 2. RELATED WORKS

Previous research in cryptographic protocols utilized watermarking scheme to embed the information into the image. Unfortunately, there is an issue with data type compatibility between the public-key cryptosystem and the targeted object of operation (frequency domain) in those protocols which use the algebraic property of an integer and real number respectively. Therefore, it is difficult to embed the information with frequency co-

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efficients in encrypted domain. But almost none of previous researchers were considered to apply watermarking scheme in the protocols. For the implementation of watermarking scheme in watermarking protocol, Kuribayashi and H. Tanaka [9] proposed a new scheme that combines ownership information, a kind of binary bit stream, with frequency coefficients transformed integer type through re-quantization method in encrypted domain. In this scheme, frequency coefficients transformation by integral-processing is employed which resulting an easy watermarking application scheme in cryptographic protocol. But, due to the larger reconstruction of quantization table based on the original image, this scheme is vulnerable to JPEG compression attack by the original quantization table, which usually processed in the size of 8×8 pixels. Moreover, the watermarks are easily removed by JPEG compression and reverse of even and odd number, because after pre-setting a quantization coefficient to the nearest even number, a re-quantized coefficient is added to '1' when the embedded bit is '1', otherwise it is leaved intact. Fig. 1 shows re-quantization method. And Lee et al. [10,11] proposed another watermarking scheme for 3D vector contents in the Anonymous buyer seller watermarking protocol. Basically, this method works in the memon’s [7] buyer seller watermarking protocol. But in this watermarking scheme, to guarantee buyer’s anonymity in the purchase process, Lei’s watermarking generation sub protocol is applied. So this scheme can overcome piracy tracing, customer's right, and unbinding problems. Other related method which has an important role in the proposed method is homomorphic encryption based on bilinear pairing on elliptic curve. It is a form of encryption where one can perform a specific algebraic operation on the plaintext by performing an algebraic operation on the ciphertext. In 2007, Goh [12] proposed a homomorhic encryption using bilinear map on elliptic curve. This

Fig. 1. Requantization procedure.

cryptographic security scheme has been proven by its ability to solve the difficult subgroup decision problem on elliptic curve. It is similar to Paillier and Okamoto-Uchiyama cryptosystem. In this algorithm, key generation, encryption, decryption and homomorphic properties are elaborated as follows. - Key generation 1. G : bilinear group order n = q1q2 on ell. curve over Fp . Q e : binear map, e : G ´ G ® G1 , q1 , q2 : prime q

2. Select q,u Î G , compute h = u 2 (Þ h order q1 ) 3. Public Key, pk = (n,G,G1 ,e,g,h) / Secret Key, sk = q1

- Encryption 1. Select random r from Z n . 2. Output C = g m h r Î G. Q m : plain text, m Î Z n .

- D ecryption 1. Let C q1 = ( g m h r ) q1 = ( g q1 ) m 2. Output m = D log of C

q1

; v = g q1

base v.

- H omomorphic properties 1. Addictively homomorphic property

E (a) = A = g a h r and E (b) = A = g b h s

E ( a + b) = g ( a +b ) h t E (a) × E (b) = A × B = g a h r g b h s = g ( a +b ) h ( r + s ) \ E (a + b) = E (a) × E (b)

2. Multiplicatively homomorphic property

Let h = g αq2 , g1 = e( g,g ) , h1 = e( g,h) Pick random t Î Z n Compute C = e( A,B) × h1t = g1ab h1r' Î G1

And many buyer-sellers watermarking protocols have proposed and the literature is rich in the

DCT and Homomorphic Encryption based Watermarking Scheme in Buyer-seller Watermarking Protocol

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Fig. 2. Block diagram of the proposed watermarking scheme.

Fig. 3. Region segmentation in a block.

relevant area [13-18]. Since the first introduction of the concept, several alternative design solutions have following problems; 1. The piracy tracing problem 3. The unbinding problem. 4. The conspiracy problem 5. The anonymity problem

In the Table 1, the feature of several buyer-seller watermarking protocols are explained.

3. PROPOSED WATERMARKING SCHEME

In buyer-seller watermarking protocol, generally the protocol consists of 3-party nodes which include the buyer, the seller, and reliable certification authority. Also according to procedure of the protocol, it is divided into three sub-protocols. They are watermark generation protocol, watermarking protocol and dispute resolution protocol. We focused our research on watermarking protocol to apply watermarking scheme in encrypted do-

Table 1. Feature of buyer-seller watermarking protocols

Protocol Piracy tracing Customer's right Unbinding Conspiracy Dispute resolution Anonymity

Proposed

○ ○ ○ ○ ○

Memon

○ ○

Ju et al. Choi et al. Goi et al. Lei et al. Shao

○ ○ ○

○ ○

○ ○ ○

○ ○ ○

○ ○ ○

○ ○



Ibrahim

○ ○ ○ ○

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main.

is calculated considering frequency, luminance and contrast sensitivity based on HVS (human visual system). We apply Watson’s method [10] due to its well performance. But, for the improvement of calculating speed, we apply S. Suthaharan’s method [11] to obtain frequency sensitivity. Next, using partitioned regions and JND, embedded blocks are chosen adaptively according to the following rules.

Firstly, the buyer creates two keys, encryption key pk B and decryption key sk B . And the buyer encrypts embedded watermark w with encryption function E ( ) . Secondly, the seller receives encrypted watermark E (w) and pk from the buyer and encrypts contents for sale, contents , with E pk ( ) . So, E pk (contents) is formed. Then, the sellZ n ,V = {k p , q , n | k p , q , n ³ Tp , q , n , 1 < p < 8, 0 £ q < 2} (1) er combines E pk (w) with E pk (contents) through Z n , H = {k p , q , n | k p , q , n ³ Tp , q , n , 0 £ p < 2, 1 < q < 8} (2) E ( w ) Å E ( contents ) the homomorphic operation and sends pk pk Z n , D = {k p , q , n | k p , q , n ³ Tp , q , n , 2 £ p < 8, 2 < q < 8} (3) ( w) Å E pk (contents) to the buyer where “ Å” is a linear Yn , JND = {k p , q , n | k p , q , n Î Z n ,V , Z n , H and Z n , D } (4) operator. At this time, due to homomorphic opern(Y ) ³ Th. ì Embedding J n = )í= E pk ( w Å contents) n. JND ation on public-key cryptosystem, E pk (w) Å E pk (contents (5) î Non - embedding otherwise ( w) Å E pk (contents) = E pk ( w Å contents) . Finally, the seller Where J n the n-th block in an image is, k p, q, n sends the encryption contents E pk ( w Å contents) to is frequency coefficient in each block J n . And Th. the buyer and the watermarked contents can be is threshold. When J n is chosen for the watermark obtained with decryption function D ( ) . embedding, the watermarked image coefficient pk B

pk B

B

B

B

B

B

B

E pkB

B

B

B

E pkB

B

B

B

B

B

sk B

3.1 Embedding scheme

In image watermarking, the existing techniques can be classified into two broad categories based on their working domain, they are spatial-domain and frequency-domain techniques. Generally, it is known that frequency-domain watermarking schemes are stronger than spatial-domain one about requirements of the watermarking techniques i.e. robustness, invisibility, etc. Therefore, on a block-DCT framework, our proposed scheme is to embed watermarks into suitable frequency coefficients using JND threshold and is designed with consideration of blind detection. The embedding process is as follows: 1) Adaptive decision of the watermarked blocks: First, we get frequency coefficients using block DCT, the size of block is 8×8, and then each block is separated into vertical, horizontal and diagonal regions as shown in Fig. 4. For the analysis of the distribution characteristic of AC components, JND (just noticeable difference)

k& p , q , n

is determined using equation (6).

ìk1,0, n ï k& p , q , n = ík0,1, n ïk î 1,1, n

n( Z n ,V ) = max[n( Z n ,V ), n( Z n , H ), n( Z n , D )] n( Z n , H ) = max[n( Z n ,V ), n( Z n , H ), n( Z n , D )]

(6)

n( Z n , D ) = max[n( Z n ,V ), n( Z n , H ), n( Z n , D )]

2) Dividing DCT coefficients into integer and decimal layers: Considering watermark insertion

based on public-key cryptosystem, in this step, we divide frequency coefficients which appear as real number into integer and decimal layers with the decimal layer is modified integer type through integral-processing as shown in equation (8). k p , q , n = k pI , q , n + k pD, q , n

(7)

Int.(k pD, q , n ) = k pD, q , n ´ 10l

(8)

Where k is interger part on k , k is Decimal part and Int.(k ) is the integer type one about k pD,q,n . l is the length of significant figures under a decimal point. I p,q,n

p,q,n

D p,q,n

D p,q,n

3) Watermark insertion: Through the previously mentioned step, the obtained layers are combined

DCT and Homomorphic Encryption based Watermarking Scheme in Buyer-seller Watermarking Protocol

with encrypted water- marks using (9)~(17). e p , q , n = ((100 - q ) / 50 ´ Qu , v ) / 2 (9) If watermark = 1 and

k& p , q , n = k1, 0, n or k0,1, n ,

then

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cryption key. Z n ,V = {k p , q , n | k p , q , n ³ Tp , q , n , 1 < p < 8, 0 £ q < 2}

(18)

Z n , H = {k p , q , n | k p , q , n ³ Tp , q , n , 0 £ p < 2, 1 < q < 8}

(19)

Z n , D = {k p , q , n | k p , q , n ³ Tp , q , n , 2 £ p < 8, 2 < q < 8}

(20)

Yn , JND = {k p , q , n | k p , q , n Î Z n ,V , Z n , H and Z n , D }

(21)

Q (= Q0,1 ) ì 1 n(Yn. JND ) ³ Th. and | | k1, 0, n | - | k0,1, n | |³ 1, 0 ïï 2 wn = í Q1, 0 (= Q0,1 ) ï0 n(Y ) ³ Th . and | | k | | k | | < n. JND 1, 0 , n 0 ,1, n 2 îï

(22)

Where wn is extracted watermark and Q is quantization table. We alter AC1, AC2 and AC4 that have same quantization step size and design. The difference between AC1 and AC2 is more than or equal to Q / 2 in the watermark embedding process. So, using equation (18)~(22), watermarks can be extracted simply. p,q

p ,q

Fig. 4. Compression quality q vs. BER (Bit Error Rate).

k ¢pI, q , n = sign(k&p , q , n ) × (| k&pI , q , n | +e pI , q , n )

(10)

k ¢pD, q , n = sign(k& p , q , n ) × ( Int.(| k& pD, q , n |) + Int.(e pD, q , n ))

(11) (12)

I q, p,n



= sign(k&q , p , n ) × (| k&

I q, p,n

I q, p,n

| -e

)

kq¢D, p , n = sign(k&q , p , n ) × ( Int.(| k&qD, p , n |) - Int.(eqD, p , n ))

else if watermark = 1 and

k& p , q , n = k1,1, n ,

(13)

then

k ¢pI, q , n = sign(k&p , q , n ) × (| k&pI , q , n | +e pI , q , n )

(14)

k ¢pD, q , n = sign(k& p , q , n ) × ( Int.(| k& pD, q , n |) + Int.(e pD, q , n ))

(15) (16) (17)

I 1, 0 , n



= sign(k&1,0, n ) × (| k&

I 1, 0 , n

I 1, 0 , n

| -e

)

k1¢,D0, n = sign(k&1, 0, n ) × ( Int.(| k&1D, 0, n |) - Int.(e1D, 0, n ))

else Non-embedding Where k ¢ and k ¢ come k& and k& , I p,q,n

I p,q,n

are watermarked and beQ is quantization table.

D p,q,n

D p,q,n

p,q

3.2 Extracting scheme

The extraction process is simple. Because watermarked contents that are delivered to the buyer after the watermark embedding process are decrypted. So, watermark extraction process is performed simply without encryption and de-

4. EXPERIMENTAL RESULTS

In these experiments, we use five MATLAB standard images that have different frequency characteristics "Airplane", "Barbara", “Co”, Girl”, and "Gold". They have 256 level gray level with the size of 512×512. For the embedded information we use a combination of the English alphabets and Arabian figures which have been converted into the bit stream using 8 bit extended ASCII codes. In all experiments, the number of characters of embedded information was 35, and the length of the converted bit stream was 280. At the same time, we scrambled each bit for the watermarking security. We set the threshold value (Th.=5) and the quality factor (q=10)considering robustness of watermarks against JPEG compression in the following simulations. To evaluate the proposed watermarking scheme, we estimated the invisibility parameter using PSNR (peak signal-to-noise ratio) between original images and watermarked one and evaluate robustness against JPEG compression by measuring number of error bits in watermarks as shown in Table 2 and Fig. 4.

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Table 2. The number of watermark-allowable blocks, embedded bits, and PSNR in each image

Image Watermark allowable block PSNR

Airplane 2026 52.36

In JPEG compression simulations, error bits appeared when quality factor q is 50, but, because we inserted same watermarks several times over and set q = 10, it is possible to extract watermarks until quality factor q reach 10. 5. CONCLUSIONS

Watermarking scheme which is based on DCT and homomorphic encryption has some application difficulties in buyer-seller watermarking protocol due to incompatibility of data type in public-key cryptosystem. We learned that Kuribayashi and H. Tanaka's scheme employed integral-processing quantization to transform frequency coefficients which make it easier to apply watermarking scheme in cryptographic protocol but unfortu-

Barbara 2725 48.93

Co 3025 45.66

Girl 2519 47.53

Gold 3228 44.61

nately, this method also showed some disadvantages in robustness issue due to its watermarks are easily removed by JPEG compression and reverse of even and odd number. To improve the robustness and invisibility of the previously available method, the author proposed a new watermark embedding algorithm into frequency coefficients considering edge-properties of each block with JND threshold. Also, the author managed to perform embedding process by divided frequency coefficients into integer and decimal layer and modified decimal layer into integer type, damage of frequency information is less than Kuribayashi and H. Tanaka's scheme. Moreover, by considering the size of general contents and watermarks after encryption procedure, the amount of insertion bit is relatively small in proposed scheme.

Fig. 5. Original image Airplane (top-left), watermarked image(top-right), watermark allowable block(bottom-left), difference image between original and watermarked one(bottom-right).

Fig. 6. Original image Barbara (top-left), watermarked image(top-right), watermark allowable block(bottom-left), difference image between original and watermarked one(bottom-right).

DCT and Homomorphic Encryption based Watermarking Scheme in Buyer-seller Watermarking Protocol

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Fig. 7. Original image Co (top-left), watermarked image (top-right), watermark allowable block (bottom-left), difference image between original and watermarked one(bottom-right).

Fig. 8. Original image Girl (top-left), watermarked image (top-right), watermark allowable block (bottom-left), difference image between original and watermarked one (bottom-right).

Fig. 9. Original image Gold (top-left), watermarked image (top-right), watermark allowable block(bottom-left), difference image between original and watermarked one (bottom-right).

Therefore, further research about techniques that can increase the amount of insertion information is needed in the future. REFERENCES

[ 1 ] M.D. Swanson, M. Kobayashi, and A.H. Tewfik, “Multimedia Data Embedding and Watermarking Technologies,” Proceedings of the IEEE, Vol. 86, No. 6, pp. 1064-1087, 1998. [ 2 ] C.I. Podilchuk and W. Zeng, “Image-adaptive Watermarking using Visual Models,” IEEE

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Proceeding of the First International Workshop on Information Hiding, pp. 49-64, 1996.

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EUROCRYPT’96, LNCS 1592, pp. 150-164,

1996. [ 6 ] B. Pfitzmann and M. Waidner, “Anonymous Fingerprinting,” Advances in Cryptology, EUROCRYPT’97, LNCS 1233, pp. 88-102, 1997. [ 7 ] N. Memon and P.W. Wong, “A Buyer-seller Watermarking Protocol,” IEEE Transactions on Image Processing, Vol. 10, No. 4, pp. 643649, 2001. [ 8 ] C.L. Lei and M.H. Chan, “An Efficient Anonymous Buyer-Seller Watermarking Protocol,”

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[10] K.G. Kwon, J.H. Lee, S.H. Lee, and K.R. Kwon, “POCS based Digital Watermarking in Buyer-seller Watermarking Protocol,” Journal of Korea Multimedia Society, Vol. 10, No. 5, pp. 569-582, 2007. [11] S.H. Lee, S.G. Kwon, and K.R. Kwon, “Geometric Multiple Watermarking Scheme for Mobile 3D Content based on Anonymous Buyer-seller Watermarking Protocol,” Journal of Korea Multimedia Society, Vol. 12, No. 2, pp. 244-256, 2009. [12] E.J. Goh, Encryption Schemes from Bilinear Maps, Doctor’s Thesis of Stanford University

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of Computer Science, 2007. M. Deng, T. Bianchi, A. Piva, and B. Preneel, “An Efficient Buyer-Seller Watermarking Protocol based on Composite Signal Representation,” Proceedings of the 11th ACM Workshop on Multimedia and Security, ACM MM&Sec., pp. 9-18, 2009. V.V. Das and J.F. Rahman, “An Enhanced Privacy Preserving Buyer-seller Protocol for Anonymous Transaction,” ACEEE International Journal on Communication, Vol. 1, No. 2, pp. 57-61, 2010. A. Rail, J. Balasch, and B. Preneel, “A Privacy-preserving Buyer–seller Watermarking Protocol based on Priced Oblivious Transfer,” IEEE Transactions On Information Forensics and Security, Vol. 6, No. 1, pp. 202-212, 2011. S. Wu and Q. Pu, “Comments on a Buyerseller Watermarking Protocol for Large Scale Networks,” International Journal of Network Security, Vol. 14, No. 1, pp. 53-58, 2012. Bjorn Terelius, “Towards Transferable Watermarks in Buyer-seller Watermarking Protocols,” IEEE International Workshop on Information Forensics and Security, pp. 197202, 2013. F. Guo, Y. Mu, and W. Susilo, “Subset Membership Encryption and its Applications to Oblivious Transfer,” IEEE Transactions on Information Forensics and Security, Vol. 9, No. 7, pp. 1098-1107, 2014.

DCT and Homomorphic Encryption based Watermarking Scheme in Buyer-seller Watermarking Protocol

Teak-Young Seong received a B.S. and a M.S. degrees from Busan University of Foreign Studies in 2004 and 2006 respectively. He is doing a Ph. D. course in Interdisciplinary Program of Information Security at Pukyong National University. His research interests include multimedia signal and image processing, digital watermarking.

Gi-Chang Kwon received a B.S., a M.S., and Ph.D. degrees from Andong National University in 1985, Daegu Univsrsity in 1993, and Yeongnam University in 2000. Currently, he is a professor in Department of IT Cooperative System at Geongbuk Provincial College. His research interests include multimedia contents and image processing, digital contents and smart system.

Suk-Hwan Lee He received a B.S., a M.S., and a Ph. D. degrees in Electrical Engineering from Kyungpook National University, Korea in 1999, 2001, and 2004 respectively. He is currently an associate professor in Department of Information Security at Tongmyong University. His research interests include multimedia security, digital image processing, and computer graphics.

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Kwang-Seok Moon He received the B.S., and M.S., and Ph.D degrees in Electronics Engineering in Kyungpook National University, Korea in 1979, 1981, and 1989 respectively. He is currently a professor in department of Electronic engineering at Pukyong National University. His research interests include digital image processing, video watermarking, and multimedia communication.

Ki-Ryong Kwon He received the B.S., M.S., and Ph.D. degrees in electronics engineering from Kyungpook National University in 1986, 1990, and 1994 respectively. He worked at Hyundai Motor Company from 1986-1988 and at Pusan University of Foreign Language from 19962006. He is currently a professor in Department of IT Convertgence and Application Engineering at the Pukyong National University. He has researched University of Minnesota in USA on 2000-2002 with Post-Doc. and Colorado State University on 2011-2012 with visiting professor. He is currently the General Affair Vice President of Korea Multimedia Society. His research interests are in the area of digital image processing, multimedia security and watermarking, bioinformatics, weather radar information processing.