A New Watermark Approach for Protection of Databases

Hazem M. El-Bakry

Faculty of Computer Science & Information Systems, Mansoura University, EGYPT

E-mail: helbakry20@yahoo.com

Nikos Mastorakis

Technical University of Sofia, BULGARIA

Abstract:

In this paper, a new approach for protecting the ownership of relational database is presented. Such approach is applied for protecting both textual and numerical data. This is done by adding only one hidden record with a secret function. For each attribute, the value of this function depends on the data stored in all other records. Therefore, this technique is more powerful against any attacks or modifications such as deleting or updating cell values. Furthermore, the problems associated with the work in literature are solved. For example, there is no need for additional storage area as required when adding additional columns especially with large databases. In addition, in case of protecting data by adding columns, we need to add a number of columns equal to the number of data types to be protected. Here, only one record is sufficient to protect all types of data. Moreover, there is a possibility to use a different function for each field results in more robustness. Finally, the proposed technique does not have any other requirements or restrictions on either database design or database administration.

Keywords: Relational Database, Copyright Protection, Digital Watermarking.

I. Introduction

The copyright protection inserts evidence into the digital objects without lossless of its quality. Whenever, the copyright of a digital object is in question, this information is extracted to identify the right full owner. Digital watermarking is the solution of embedding information in multimedia data. There are many techniques used to protect copyrights [18].

Digital contents in the form of text

document, still images motion picture, and music etc. are widely used in normal life nowadays. With the rapid grown of internet users, it boots up transaction rates (file sharing, distribution or change). Trend goes up dramatically and continues growing everyday due to convenient and easy to access. It is, hence, copyright protection becomes more concerned to all content owners [1-2].

Watermark is an open problem that aimed

to one goal. This goal is how to insert [error/ mark/ data/ formula/ evidence/ so on] associated with a secret key known only by the data owner in order to prove the ownership of the data without lossless of its quality.

In order to evaluate any watermark

system, the following requirements are generally considered in prior: (i) Readability: A watermark should convey as much information as possible,

statistically detectable, enough to identify ownership and copyright unambiguously, (ii) Security: Only authorized users access to the watermark data, (iii) Imperceptibility: The embedding process should not introduce any perceptible artifacts into original image and not degrade the perceive quality of image, and (iv) Robustness: The watermark should be able to withstand various attacks while can be detected in the extraction process.

In general, watermark is small, hidden

perturbations in the database used as an evidence of its origin. Inserting mark into original data used to demonstrate the ownership. Watermark should not significantly affect the quality of original data and should not be able to destroy easily. The goal is to identify pirated copies of original data. Watermarking does not prevent copying, but it deters illegal copying by providing a means of establishing the ownership of a redistributed copy. There are more approaches and algorithms available for image, audio and video but the new is how to introduce a new approach serve the relational databases?

Agrawal et al. introduce a watermarking

technique for numerical data [1]. This technique dependent on a secret key, uses markers to locate tuples to hide watermark bits, hides watermark bits in the least significant bits. Also Sion et al. introduce a watermark technique for numerical data [2]. This technique is dependent on a secret

Proceedings of the 9th WSEAS International Conference on APPLIED INFORMATICS AND COMMUNICATIONS (AIC '09)

ISSN: 1790-5109 243 ISBN: 978-960-474-107-6

key, instead of primary key uses the most significant bits of the normalized data set, divides the data set into partitions using markers, and varies the partition statistics to hide watermark bits.

Relational database was selected because

it is common and was created before. Watermarking for values of selected attributes in tuples of relational database, it must be small to be tolerated [3,4].

This paper is organized as follows: The

problem statement is described in section II, Section III presents the proposed technique and discusses the evaluation of this novel technique.

II. Watermarking for Databases

Watermarking of relational databases is very important point for the researches; because the free databases available on the internet websites are published without copyrights protection and the future will exploding problems. If the database contains very important data; then the problem will be how to add watermark to the numerical or textual data in relational database. This should be performed without affecting the usefulness and the quality of the data.

The goal is how to insert intended error

/mark /data /formula/ evidence associated with secret key known only by the data owner in order to prove the ownership of the data without lossless of its quality [5,6]. Fig.1 shows a typical watermark model for any relational database. Watermark W is embedded into the relational database I with a secret key k, the watermarked relational database IW later pass through a distribution channel (computer network, internet, etc.), which are simulated under several kinds of common attacks. The watermarked database after attack IW, with the same secret key, will then extracted in order to recover the original watermark data W [4-10].

III. The Proposed Technique

Generally, the proposed technique relies on changing database schema; which is the model of database contents, thus the structure of the data will be changed by adding a new record (altering the table) relies on the original data in each field of the relational databse. The function used in constructing the new record as well as the secret key known only by the data owner. In general, the function used in protecting this relational database is locked via a predefined secret key. The proposed technique can be

summarized in the following steps:

1. Get the relational table from the desired database; which must be numeric values.

2. For each field, adding a new calculated record based on the data stored in other records with a secret function f(.).

3. Generate the secret function f(.); which depends on the numeric values of the other cells in the current field in an encrypted structure.

4. Apply this function to the remaining fields in the table; thus an extra record has been created and added to the original database table.

5. Protect the calculated column from attack with a protection KEY known only to the data owner.

6. The added record may be hidden to malicious.

In general, the proposed technique can be

used to protect the ownership of the relational database that contains only numeric values. This novel technique adds only one hidden record with a secret function. Not only that but also locking this calculated row from any attacks or changes such as deleting or updating. The advantages of the proposed technique are:

1. The proposed technique is available for any relational database. 2. No delay and no additional time required till the normal calculation end. 3. Allowable for any update such as adding rows and changing the values of the columns. 4. Not allowable for deleting the hidden records because it was locked with a secret key known only by the data owner. 5. The values in the hidden record are known only by the data owner [14-16]. 6. Furthermore, there is a possibility to use a different function for each field results in more robustness. 7. Moreover, there is no need for additional storage area as required when adding additional columns as described in [18].

The relational database in Table 1 is the

North wind database used for many applications because it was mostly published on the internet and common in different Microsoft applications. Table 2 presents the watermarked relational database. The algorithm has been practically summarized in the following: (i) selecting any numerical table such as Table l (ii) adding a new record; its value relies on the data stored in other records by unknown functions, For example:

Key = STD(Cells)+ Max(Cells)- Min(Cells)±Q (1)

Proceedings of the 9th WSEAS International Conference on APPLIED INFORMATICS AND COMMUNICATIONS (AIC '09)

ISSN: 1790-5109 244 ISBN: 978-960-474-107-6

where, STD is the standard deviation, and Q is a constant value. (iii) Applying the function for all columns as shown in Table 2. (iv) Hide the calculated record and export the table with the new added record (vi) lock the entire table with a protection key known only to the data owner that deter the copying and changing the values of cells. Another example is listed in Table 3. It combines different types of data. The same principles are applied to numerical The final result is shown in Table 4. A code for each character is given as listed in Table 5. The secret formula is calculated as follows:

n

n

i jji

i

∑ ∑= == 1 1

α

ραβ (2)

where, α is the number of characters per word, ρ is the character code, n is the number of words, and β is the secret key. The resulted Emp_name and address can be concluded as shown in Table 6.

IV. Conclusions A novel digital watermarking technique

for relational database has been presented. The proposed technique has provided a very high degree of reliability and protection of relation database with the aid of the user predefined function; which inserts an additional hidden record to available relational database. This technique has many advantages over existing techniques. First, it is available for any relational database. Second, it does not require any additional time because the calculations required for the new record are done off line. Third, it is not possible to delete the hidden record because it has been locked with a secret key known only by the data owner. The values in the hidden record are known only by the data owner. Furthermore, the problems associated with the work in literature are solved. For example, there is no need for additional storage area as required when adding additional columns especially with large databases. In addition, in case of protecting data by adding columns, we need for to add a number of columns equal to the number of data types to be protected. Here, one record is sufficient to protect all types of data. Moreover, there is a possibility to use a different function for each field results in more robustness. Finally, the proposed technique does not have any other requirements or restrictions on either database design or database administration.

References [1] Chirawat Temi, Choomchuay Somsak, and

Attasit Lasakul, "A Robust Image Watermarking Using Multiresolution Analysis of Wavelet," Proceeding of ISCIT-(2000)

[2] C. S. Collberg and C. Thomborson.Watermarking, Tamper-Proofing, and Obfuscation-Tools for Software Protection. TechnicalReport 2000-03,University ofArizona, Feb (2000).

[3] D. Gross-Amblard. "Query-Preserve Watermarking of Relational Databases and XML Documents," In PODS 03: Proceedings of the 22nd ACM SIGMODSIGACT-SIGART Symposium on Principles of Database Systems, PP. 191-201, ACM Press, (2003).

[4] "Digital Signatures in Relational Database Applications" online available at GRANDKELL systems INC. www.gradkell.com.(2007)

[5] I. J. Cox andM. L.Miller. A review of watermarking and the importance of perceptual modeling. In Proc. of Electronic Imaging, February 1997.

[6] I. Cox, J. Bloom, and M. Miller. "Digital Watermarking," Morgan Kaufinann, (2001).

[7] Jerry Kiernan, Rakesh Agrawal, "Watermarking Relational Databases," Proc. 28"' International Conference. Very Large Databases VLDB, (2002).

[8] L. Boney, A. H. Tewfik, and K. N. Hamdy. Digital watermarks for audio signals. In International Conference on Multimedia Computing and Systems, Hiroshima, Japan, June (1996).

[9] M. Atallah and S. Wagstaff. Watermarking with quadratic residues. In Proc. of IS&T/SPIE Conference on Security and Watermarking of Multimedia Contents, January (1999).

[10] M. Atallah, V. Raskin, C. Hempelman, M. Karahan, R. Sion, K. Triezenberg, and U. Topkara., "Natural Language Watermarking and Tamper-proofing" The Fifth International Information Hiding Workshop, Florida, USA, (2002).

[11] Ming-Shing Hsieh, Din-Chang Tseng, and Yong Huai Huang, "Hiding Digital Watermarking Using Multiresolution Wavelet Transform," IEEE Trans. On Industrial Electronics, Vol. 48, No.5, October (2001).

[12] M. Shehab, E. Bertino, and A. Ghafoor, "Watermarking Relational Databases Using Optimization Based Techniques," CERIAS Tech Report-(2006).

[13] Radu Sion, Mikhail Atallah, Fellow, IEEE,

Proceedings of the 9th WSEAS International Conference on APPLIED INFORMATICS AND COMMUNICATIONS (AIC '09)

ISSN: 1790-5109 245 ISBN: 978-960-474-107-6

and Sunil Prabhakar, "Rights Protection for Relational Data," IEEE Trans. On Knowledge and Data Engineering, Vol. 16, No. 6, June (2004)

[14] R. Sion, M. Atallah, and S. Prabhakar, "Rights Protection for Relational Data," IEEE Transactions on Knowledge and Data Engineering, Volume 16, Number 6, June (2004).

[15] S. Benjamin, B. Schwartz, and R. Cole. Accuracy of ACARS wind and temperature observations determined by collocation. Weather and Forecasting, 14:1032-1038, (1999).

[16] W. Bender,D. Gruhl, and N.Morimoto. Techniques for data hiding. In Proc. of the

SPIE 2420 (Storage and Retrieval for Image and Video Databases III), pages 164-173, (1995).

[17] Y. Li, V. Swarup, and S. Jajodia, " Fingerprinting Relational Databases: Schemes and Specialties," IEEE Transactions on Dependable and Secure Computing, Vol. 02, No. 1, PP.34-45, Jan-Mar (2005).

[18] G. H. Gamal, M.Z. Rashad and M.A. Mohamed, " A Simple Watermark Technique for Relational Database," Mansoura Journal for Computer Science and Information Systems Vol. 4, No. 4, Jan 2008.

Fig.1 Typical Watermark System Model

Table 1: The original relational database

Stock No. Jan. Feb. Mar. Apr. May June July Aug. Sep. Oct. Nov. Dec.

125970 1400 1100 981 882 794 752 654 773 809 980 3045 19000 212569 2400 1721 1414 1191 983 825 731 653 723 790 1400 5000 389123 1800 1200 890 670 550 450 400 410 402 450 1200 16000 400314 3000 2400 1800 1500 1200 900 700 650 1670 2500 6000 15000 400339 4300 2600 1800 1600 1550 895 700 750 900 8000 24000 400345 5000 3500 2800 2300 1700 1400 1000 900 1600 3300 12000 20000 400455 1200 900 800 500 399 345 300 175 760 1500 5500 17000 400876 3000 2400 1500 1500 1300 1100 900 867 923 1100 4000 32000 400999 3000 1500 1000 900 750 700 400 350 500 1100 3000 12000 888652 1234 900 821 701 689 621 545 421 495 550 4200 12000

Proceedings of the 9th WSEAS International Conference on APPLIED INFORMATICS AND COMMUNICATIONS (AIC '09)

ISSN: 1790-5109 246 ISBN: 978-960-474-107-6

Table 2: The watermarked relational database

Stock No. Jan. Feb. Mar. Apr. May June July Aug. Sep. Oct. Nov. Dec.

125970 1400 1100 981 882 794 752 654 773 809 980 3045 19000 212569 2400 1721 1414 1191 983 825 731 653 723 790 1400 5000 389123 1800 1200 890 670 550 450 400 410 402 450 1200 16000 400314 3000 2400 1800 1500 1200 900 700 650 1670 2500 6000 15000 400339 4300 2600 1800 1600 1550 895 700 750 900 8000 24000 400345 5000 3500 2800 2300 1700 1400 1000 900 1600 3300 12000 20000 400455 1200 900 800 500 399 345 300 175 760 1500 5500 17000 400876 3000 2400 1500 1500 1300 1100 900 867 923 1100 4000 32000 400999 3000 1500 1000 900 750 700 400 350 500 1100 3000 12000 888652 1234 900 821 701 689 621 545 421 495 550 4200 12000 564646 3433 2062 1340 994 1298 1362 553 715 1714 2167 5235 14200

Table 3: The original relational database

Emp_ID Emp_Name Address Birth Date Salary 2324 Ahmed Mansoura 17/11/1987 2320 4547 Nagi Tanta 22/02/1989 1344 6549 Sameh Cairo 12/12/1987 2456 7653 Kamel Sudan 10/08/1986 1233 8975 Alaa Cairo 04/10/1981 2356

Table 4: The watermarked relational database

Emp_ID Emp_Name Address Birth Date Salary 2324 Ahmed Mansoura 17/11/1987 2320 4547 Nagi Tanta 22/02/1989 1344 6549 Sameh Cairo 12/12/1987 2456 7653 Kamel Sudan 10/08/1986 1233 8975 Alaa Cairo 04/10/1981 2356 5661 Tamer Banha 01/19/1994 2164

Table 5 : Alphabetic Character Coding

Character Code (ρ) Character Code (ρ) A B C D E F G H I J K L M

1 2 3 4 5 6 7 8 9

10 11 12 13

N O P Q R S T U V W X Y Z

14 15 16 17 18 19 20 21 22 23 24 25 26

Proceedings of the 9th WSEAS International Conference on APPLIED INFORMATICS AND COMMUNICATIONS (AIC '09)

ISSN: 1790-5109 247 ISBN: 978-960-474-107-6

Table 6: The computed secret key and its corresponding Emp_name and address

Secret key (β) Emp_Name Address

1:50 Mohamed Sinai 51:100 Ali Talkha

101:150 Hassan Sandoub 151:200 Tamer Banha 201:250 Shaker El-Baramoon

Proceedings of the 9th WSEAS International Conference on APPLIED INFORMATICS AND COMMUNICATIONS (AIC '09)

ISSN: 1790-5109 248 ISBN: 978-960-474-107-6