1. A DCT Quantization-Based Image Authentication System for Digital Forensics
I-Chuan Chang Bor-Wen Hsu and Chi Sung Laih
Institute of Computer and Communication, National Cheng Kung University
Tainan, TAIWAN, Republic of China,2005 IEEE
報告人：張淯閎

2. Outline Abstract Digital forensic procedure
Improved Image Authentication Schemes
Improved Detection Schemes 1(IDS-1)
Improved Detection Schemes 2(IDS-2)
UCID
Experiment
Comparison
Conclusion

3. Abstract
This paper proposed an integrated image authentication system for digital forensics.
Improving the detection problems of a DCT quantization-based image authentication scheme.

4. Digital forensic procedure
Digital data is easily manipulated with ubiquitous software.
Digital data is used as the evidence in court, demanding for authenticity assurance and detection.

5. Digital forensic procedure

6. Improved Image Authentication Schemes
Using the error correction code(ECC),watermarking and cryptographic hash is proposed by Qubin Sun.
They denote a DCT coefficient before quantization as F(i), and coresponding value in the quantization table as Q(i), the output of quantizer as quotient F(i), and remainder R(i) respectively.

7. Improved Image Authentication Schemes
Maximum absolute magnitude of noise is denoted as N.
DCT values originally closed to nQ will be pushed to the opposite side, and thus the sign changes due to acceptable manipulations.
The change to the DCT value is large, pushing the value from “-“ side of nQ to “-“ side of any multiple of Q.

8. Improved Detection Schemes 1(IDS-1)
In order to solve the detection problems, we propose using the detection code (DO) instead of the correction code (CO) to detect the error of the image.
Generate random sequence sji continuously with the secret key Ks. When the i-th DCT coefficient in the j-th block, Fj O(i), is selected as the content feature, every possible quantization value, Fj O(i), will have its corresponding bit, sji(Fj O(i)).

9. Improved Detection Schemes 1(IDS-1)
In the verification process, to begin with, generate random sequence sji with the same secret key Ks as used in the authentication process.
Use CO to modify the received content feature to the appropriate value, FjR(i), and get the quantized value, FjR(i).

10. Improved Detection Schemes 2(IDS-2)
The quantization value of the content features of each block, FjO(i), are used as the input of the hash function with the secret key, Ks, as the initial value.The output, HjO, is the detection code of j-th block.
In the verification process, use CO to modify the received content feature to the appropriate value, FjR(i), and get FjR(i). Then Fj R are used as the input of the hash function with the same secret key, Ks, as the initial value.

13. UCID (Uncompressed Colour Image Database)
The UCID dataset currently consists of 1338 uncompressed images and each image is full-color with 512x384 pixels.
The images of UCID not only have sufficient quantity but also have common contents which are much similar to the snapshots taken by people or any surveillance system.

15. Experiment 1

16. Experiment 2

17. Comparison
546

18. Conclusion
A thorough image authentication system is proposed and depicted in details for digital forensic application.
Two improved detection schemes to tackle the problems of original detection scheme ,solving the problem of detecting the correct region as the manipulated one in the original detection scheme.
The proposed image authentication system is supposed to provide the trustworthy information of the digital image evidence to enhance the legitimacy of the verdict in the legal system.