This presentation proposes a remote biometric authentication system using video-object steganography over wireless networks. It uses principal component analysis (PCA) and discrete wavelet transform (DWT) to encrypt biometric signals, hide them in video objects, and transmit them securely. The encrypted biometric signals are inserted into the most significant wavelet coefficients of video objects during transmission. At the receiver end, fingerprint matching is used to authenticate users by extracting and decrypting the biometric signals from the video objects. The system aims to provide secure remote authentication using natural biometrics while maintaining efficiency and resistance against data loss during wireless transmission.

1. Presentation By
1) Omkar Salunke
2) Shweta Singh
3) Pranay Dhamal
4) Kuldeep Ruletiya
REMOTE AUTHENTICATION VIA BIOMETRICS:
A VIDEO-OBJECT STEGANOGRAPHIC
MECHANISM OVER WIRELESS NETWORKS
Mahatma Education Society
Pillai HOC College of Engg. & Tech., Rasayani
Department of Computer Engineering
Guidance By
Prof. Govind Rao Mettu

2. CONTENT
1) Introduction
2) Existing method
3) Proposed method
4) RSA Encryption algorithm
5) PCA Algorithm
6) DWT Algorithm
7) System Architecture
8) Advantages
9) Conclusion
10) References

3. INTRODUCTION
1. Sensitive information exchange
authentication.
2. Visual authentication with Video and audio.
3. RSA (Rivest, Shamir & Adleman).
4. PCA (Principal component Analysis).
5. DWT (Discrete Wavelet Transform).
6. IDWT (Inverse Discrete Wavelet Transform).

4. EXISTING METHODS
Remote Authentication
• In “password authentication with insecure
communication” by Lamport scheme a verification
table should be maintain on the remote server and
if intruders break into it, they can modify the
table.
• Another remote user authentication scheme
involves smart card using dynamic users identities
per transaction section.
• Biometrics are used simply as an authentication tool in
smart card technology.

5. EXISTING METHODS (CONT…)
Steganographic Method
• Steganographic includes two method:
• Digital compression transform (DCT)
• Digital wavelet transform (DWT)
• DCT & DWT related with popular digital images & video
compression scheme(i.e.,JPEG,MPEG,JPEG-2000,H264).It
is used for hiding data’s.
• Using DCT & DWT steganographic message can be send in
lossy environment, with some robustness against detection
or attack.

6. PROPOSED METHOD
• Biometric encryption using RSA algorithm.
• Employ wavelet based steganography.
• Encrypt Biometric Signal to allow for natural
authentication.
• Involves a RSA encryption to increase security.
• The encrypted biometric signal is hidden in a VO, which
can reliably be detected in modern applications that
involve teleconferencing.

7. RSA ALGORITHM
• RSA is an algorithm used by modern
computers to encrypt and decrypt messages.
• It is an Asymmetric algorithm.

8. RSA ALGORITHM (CONT…)
• Choose two large prime numbers P & Q.
• Calculate N=P*Q.
• Select the public key (i.e., the encryption key) E, such that it is not a
factor of (P-1)&(Q-1).
• Select the private key (i.e., the decryption key) D, such that the
following equation is true: (D*E) mod (P-1)*(Q-1)=1
• For encryption calculate the cipher text CT from the Plane text PT as
follows: CT=PTE mod N
• Send CT as the Cipher Text to the receiver.
• For Decryption, Calculate the Plane Text PT from the Cipher Text CT
as follows: PT=CTD mod N

9. PRINCIPAL COMPONENT ANALYSIS
(PCA)
• PCA is a standard technique for visualizing high dimensional data &
for data pre-processing.
• PCA reduce the dimensionality(the number of variables) of a data set
by maintaining as much variance as possible.
• Advantage of PCA:
• Reduce complexity in image grouping with the use of PCA.
• Reduction of noise since the maximum variation.
• Lack of redundancy of data given the orthogonal component.
• Dis-advantage of PCA:
• The covariance matrix is difficult to be evaluated in an accurate
manner.

10. DISCRETE WAVELET TRANSFORM
(DWT)
• The wavelet transform has gained wide spread acceptance
in signal processing and image compression.
• DWT decomposes signal into basic function, this function
is known as wavelet transform.
• The DWT has been introduced as a highly, efficient and
flexible method for sub band decomposition of signal.
• Three level decomposition for 2D-DWT image consist of
pixels that are arranged in 2D matrix, each pixel
represents the digital equivalent of image intensity.

11. SYSTEM ARCHITECTURE

12. SYSTEM ARCHITECTURE (CONT...)
Assuming that user X wants to be remotely authenticated,
first of all X’s video object (VO) is automatically segmented,
using a head and body detector. Next, one of X’s biometric
signal is encrypted by a RSA Algorithm. Afterwards the
encrypted signal is inserted to the most significant wavelet
coefficients of a video object, using its DWT (Discrete
Wavelet Transform). DWT provide both invisibility and
significant resistance against lossy transmissions and
compressions, conditions that are typical in wireless
networks. Finally, The Inverse Discrete Wavelet Transform
(IDWT) is entreated to provide the stego-object (SO).

13. Video Selected By Sender

14. Watermarked Video Send to Receiver

15. Fingerprint Matching and Authentication

16. Retrieved Video By Receiver

17. ADVANTAGES
• Better and Increased security.
• Better against deciphering, noise and compression.
• Ease of implementation.
• Encrypt biometric signal allow natural authentication.

18. SOFTWARE AND HARDWARE
• Software Requirements
• Front end : Matlab (v8.2.0.701) R2013b
• Back end : Matlab (v8.2.0.701) R2013b
• Operating System : Windows 10 (32bit)
• Hardware requirements
• Processor : Intel(R) Core(TM) i3-2348M CPU
@1.70GHz
• Ram : 2GB
• Hard Disk Capacity : 160GB

19. CONCLUSION
• Urgent need to further develop and integrate biometric
authentication techniques.
• The use of PCA and DWT provides high levels of
Image Processing.
• Efficient bandwidth usage.
• System is able to recover the hidden encrypted
biometric signals under different losses.
• The hash value of a biometric identifier is utilized, so
that there is a centralized authentication service.

20. REFERENCE
• L. Lamport, “Password authentication with insecure
communication,” Communications of the ACM, vol.
24, no. 11, pp. 770–772, 1981.
• W. Stallings, Cryptography and Network Security:
Principles and Practices. Prentice-Hall, 5th edition,
Upper Saddle River, NJ, USA, 2010.
• Y.-y. Wang, J.-y. Liu, F.-x. Xiao, and J. Dan, “A more
efficient and secure dynamic id-based remote user
authentication scheme,” Computer Communications,
vol. 32, no. 4, pp. 583–585, Mar. 2009.

21. REFERENCE
• M. K. Khan, S.-K. Kim, and K. Alghathbar,
“Cryptanalysis and security enhancement of a ‘more
efficient & secure dynamic id-based remote user
authentication scheme’,” Computer Communications,
vol. 34, no. 3, pp. 305–309, Mar. 2011.
• E.-J. Yoon, S.-H. Kim, and K.-Y. Yoo, “Cryptanalysis
and security enhancement of a ‘more efficient & secure
dynamic id-based remote user authentication
scheme’,” International Journal of Innovative
Computing, Information and Control, vol. 8, no. 5(B),
pp. 3661–3675, May 2012.