A study for Relational Database watermarking scheme

1. A study for Relational Database watermarking scheme Speaker: Pei-FengShiu Date: 2012/09/21

2. Outline • Introduction • Relational Database watermarking schemes • Discussion

3. Introduction • Image • Pixel(0-255) • Database • Textual data • Numerical data Compression code Pixel blocks Coefficient blocks

4. Schemes • Relational Databases Watermarking for textual and numerical data • Zhang et al., MEC2011, China, 2011. • DCT Transform based Relational Database Robust Watermarking Algorithm • Song et al., ISDPE2010, USA, 2010.

5. 2011 International Conference on MechatronicScience, Electric Engineering and Computer Relational Databases Watermarking for textual and numerical data Author: Lizhong Zhang, Wei Gao, Nan Jiang, LiqiuZhang and Yan Zhang

6. Notations and Parameters

7. Watermark embedding algorithm • Tuples selection. Condition: 40,000

8. Watermark embedding algorithm • Watermark insertion 155mod 4 = 3 Set: Hi=Hash(Key, 235)=155, e=37, =5, N=2, Watermark bit =1 1 Numerical attribute: Textual attribute: If Lni,jdigits mod 2 ≠ watermark bitthen Lni,jdigits 1 If Watermark bit =1 then Insert #13(Carriage return character) at location Lti,j Else Insert #10(Linefeed character) at location Lti,j 155mod 5 = 0

9. Watermark extracting algorithm • Tuples selection • Watermark extraction Numerical attribute: Textual attribute: Watermark bit = Lni,jdigits mod 2 If #13 at location Lti,jthen Watermark bit =1 If #10 at location Lti,j thenWatermark bit =0

10. Experimental results • Subset Addition Attack • Watermark detected ratio 99.5% • Subset Alteration Attack • Watermark detected ratio 99.5% even if 70% of the tuples of the database are modified • Subset Deletion Attack • Watermark detected ratio 95% even if 70% of the tuples are deleted.

11. 2010 Second International Symposium on Data, Privacy, and E-Commerce DCT Transform based Relational Database Robust Watermarking Algorithm Author: Song Yige, Liu Weidong, Song Jiaxing and Wong Ming Sze Angela

12. Notations and Parameters

13. Watermark embedding algorithm • Tuples selection 581,012

14. Watermark embedding algorithm • DCT transform - two-dimensional DCT • Watermark insertion • Select medium frequency coefficient as C • Inverse DCT transform • Update database If (Watermark bit =1 && C > 0 ) or (Watermark bit =0 && C < 0 ) then C = C Extracting phase: if C > 0 then Watermark bit = 0else if C < 0 then Watermark bit = 1

15. Experimental results • Subset Addition Attack Original watermark and extracted watermark after tuple deletion attack

16. Experimental results • Subset Alteration Attack Original watermark and extracted watermark after tuple deletion attack

17. Experimental results • Subset Deletion Attack Original watermark and extracted watermark after tuple deletion attack

18. Discussion • Practicality • Affect data analysis result • Affect data mining result • Effect of computing time for big data