This is adual authentication project done in matlab software.

1. `ADVANCED AUTHENTICATION USING VISUAL
CRYPTOGRAPHY AND A STEGANOGRAPHIC Via
BIOMETRICS FOR ONLINE EXAMS/INTERVIEWS

2. OBJECTIVE
 To develop a two factor authentication mechanism based on visual
Cryptographic scheme and video object Steganography via biometrics

3. INTRODUCTION
 Authentication is the act of confirming identification of someone, some application…
 Normally authentication includes the use of username, password, digital cards, signatures,
biometric attributes.
 Where biometric attributes are unique to every individual and there by used in variety of
application where there need to claim authenticity of individual
 In this system authentication is done using biometric attribute ie.,fingerprint

4.  With the rapid transmission of biometric data over internet ,the security of the data is in major concern
 To avoid these security threats and sharing issues the secret information like text ,audio ,video, image
used for authentications are applied using the techniques visual cryptography and steganography
 In this proposed system visual cryptography and steganography are implemented individually for
different attributes
 Visual cryptography is technique to generate the shares of a secret image and the secret can be achieved
by combining both shares
 Steganogtaphy is used to hide the secret image within a cover image

5. SCOPE OF THE SYSTEM
 In todays century security and authentication are the major concern in all type of application
like online exams,interview,banking..etc
 Where communicating entities are located at different locations
 To ensure the security of the systems and digital data shared , there should be a dual
authentication process
 The proposed system provides the facility with both visual cryptography and steganography
 The programing is developed using MATLAB software and presented in graphical user
interphase

6. SYSTEM OVERVIEW

7. SYSTEM OVERVIEW

8. VERIFIABLE VISUAL CRYPTOGRAPHY
• Visual cryptography is a cryptographic technique which allows visual information to be encrypted in
such a way that the decryption can be performed by the human visual system, without the aid of
computers.
• Visual cryptography scheme eliminates complex computation problem in decryption process, and the
secret images can be restored by stacking operation.
• This property makes visual cryptography especially useful for the low computation load requirement

9. • In this system we are using (2,2) VCS scheme which generate two shares of image. For input binary
image which is in 1 and 0 format.
• In the 2-out-of-2 scheme, every secret pixel of the image is converted into two shares and recovered by
simply stacking two shares together.
• This is equivalent to using the OR operation between the shares.
• First we take a monochrome image for the source. Pixels in the image are either white or black
• Next sub-divide each pixel into four smaller subpixels.
• shade these four subpixels to represent the source image, then subjectively divide them between the two
cypher images are to create.

10. • Distribute the shading such that, if you have just one of the cypher images, it is impossible to determine
what is on the other cypher image, and thus, impossible to decrypt the image.
• If the original pixel in the image is black, fill in all four sub pixels then distribute them.
• The pattern selection is random
• It does not matter which pair of pixels goes on which layer, when they are combined, all four pixels will
be black.

11. • Conversely, if the source image pixel is white, shade in just two pixels, make sure that
the same pixels are shaded on both layers.
• In this way, when the two cypher images are combined, only two pixels are shaded.
• The result of this process is two images which when combined result in an image with half the
contrast of the original.
• The black of the source remains black in the combined cypher, but the white in the source is changed
to a randomly mottled half-tone gray
• this is still sufficiently high enough contrast for the secret message to be easily read
.

12. BLOWFISH ENCRYPTION
• Image encryption is necessary for future multimedia Internet applications.
• By encrypting these images, a degree of security can be achieved.
• Blowfish is a symmetric block cipher that can be effectively used for encryption and safeguarding of
data
• It takes a variable-length key, from 32 bits to 448 bits, making it ideal for securing data.
• Blowfish Algorithm is a Feistel Network, iterating a simple encryption function 16 times
• Blowfish contains 16 rounds. Each round consists of XOR operation and a function. Each round
consists of key expansion and data encryption.

13. Algorithm: Blowfish Encryption
 Divide x into two 32-bit halves: xL, xR
 For i = 1to 16:
 xL = XL XOR Pi
 xR = F(XL) XOR xR
 Swap XL and xR
 Swap XL and xR (Undo the last swap.)
 xR = xR XOR P17
 xL = xL XOR P18
 Recombine xL and xR

14. Blowfish symmetric block cipher algorithm encrypts block data of 64-bits at a time.it will follows the
feistel network and this algorithm is divided into two parts.
• 1. Key-expansion
• 2. Data Encryption
Key-expansion:
• It will converts a key of at most 448 bits into several subkey arrays totaling 4168 bytes. Blowfish uses
large number of subkeys. These keys are generate earlier to any data encryption or decryption.
• The p-array consists of 18, 32-bit subkeys: P1,P2,………….,P1
Data Encryption:
• It is having a function to iterate 16 times of network. Each round consists of key-dependent permutation
and a key and data-dependent substitution.
• All operations are XORs and additions on 32-bit words. The only additional operations are four indexed
array data lookup tables for each round.

15. STEGANOGRAPHIC VIDEO OBJECT AUTHENTICATION
The proposed scheme involves
• Extraction of the host video object from a video and detection of the QSWTs to embed the encrypted signal,
• Embedding of the encrypted signal to the host video object using steganography
• Compression of the final content
Video to frame conversion
• The video is taken from the user as input.
• Usually, the video Consists of multiple frames. The frames are extracted by explicit values specified by the
user.
• After the conversion of video to frames, the user has to input their biometric image i.e. retinal pattern or
finger print.

16. DATA HIDING
• The goal of this system is send sensitive information that are invisible to human eyes but also robust under
different attacks.
• Qualified Significant Wavelet Trees provide such robustness in the steganography.
• The hiding module hide the encrypted the information into the largest-value QSWTs of energy-efficient
pairs of sub bands
• The image obtained is stego-object image.
• It is compressed and transmitted and receiver after receiving decompress and decryption is done to get
original information and it is accessed as a secret code.

17. • The Discrete Wavelet Transform is used to hide information like text, audio, video, images etc., into
cover image.
• The steganography technique is implemented in the discrete wavelet transform.
• In this technique the cover image is divided into four equal parts with respect to the resolution of the
image
• The four parts is represented as low, middle and high frequencies that is represented as LL, HL, LH
and HH.

18. • By applying the DWT once to an area of arbitrary shape, four parts of low, middle, and high frequencies, i.e.,
LL1, HL1, LH1, HH1, are produced.
• Band LL1 (HH1) includes low (high) frequency components both in horizontal and vertical direction, while
the HL1 (LH1), includes high (low) frequencies in horizontal direction and low (high) frequencies in vertical
direction.
• Subband LL1 can be further decomposed in a similar way into four different subbands, denoted as LL2, HL2,
LH2, HH2 respectively.
• The coefficient at the highest level is called the parent and all coefficients corresponding to the same spatial
location at the lower levels of similar orientation are called children..

19. • Select the pair of subbands that contains the highest energy content (among the three pairs),
• Pi : EPi = max(EP1 ;EP2 ;EP3 )The generalized formula
• x2(i,j)={HL2,LH2,HH2},x1(p,q)={HL1,LH1,HH1}and M,N is the size of the subbands at level two
• After selecting the pair of subbands containing the highest energy content, QSWTs are found for this pair
• If a wavelet coefficient xn(i,j) ∈ D at the is a parent of xn-1(p,q), where D is a subband
• labeled HLn, HLn, HHn, satisfy |xn(i,j)|>T1, |xn- 1(p,q)|>T2 for given thresholds T1 and T2, then xn(i,j)
and its children are called a QSWT
• The encrypted biometric signal is embedded by modifying the values of the detected QSWTs
• After the encrypted biometric image is hidden into the segmented the input image Inverse Discrete
wavelet transform is applied to combine the segmented image and produce a stego -object.

20. MINIATUIA BASED FINGERPRINT MATCHING
• Fingerprint recognition or fingerprint authentication refers to the automated method of verifying a
match between two human fingerprints
• Fingerprints are one of many forms of biometrics used to identify individuals and verify
their identity
• A fingerprint is the pattern of ridges and valleys on the finger tip.
• A fingerprint is thus defined by the uniqueness of the local ridge characteristics and their
relationships.
• Minutiae points are these local ridge characteristics that occur either at a ridge ending or a ridge
bifurcation.
• A ridge ending is defined as the point where the ridge ends abruptly and the ridge bifurcation is the
point where the ridge splits into two or more branches.

21. IMPLEMENTATION-3 PHASES
RGISTRATION
•visula cryptography
•share1(user) and share2(reciver)
LOGIN
•input video
•input fingerprint
•stego object
VERIFICATION
•stegoobject
•extract fingerprint and video object
•Fingerprint matching

22. 15.2
0.99 0.99
16.26
61.97
0.52 1 0.002
40.49
0.41 0.936
9.54
PSNR MSE SSM AVG
ANALYSIS
ENCRYPT STEGO DECRYP

23. The PSNR is measured to ensure whether the encrypted image is intelligible to unauthorized person or not.
 When comparing, PSNR is an approximation to human perception of reconstruction quality. Although a
higher PSNR generally indicates that the reconstruction is of higher quality.
 Thethreshold value for PSNR is 61.971 dB
 Whenever we are hiding image behind cover image though PSNR ratio increased so quality is not
degrading as PSNR value increasing the quality of image is also increasing.
 That is there is not no effect on original image which is hidden twice in a cover image. PSNR value
increasing image quality also increase.
PSNR

24. SSIM
• The structural similarity index is a method for measuring the similarity between two images.
• Measuring of image quality based on an initial uncompressed or distortion-free image as reference
• SSIM is designed to improve on traditional methods like peak signal-to-noise ratio (PSNR) and mean squared
error (MSE), which have proven to be inconsistent with human eye perception.
MSE
• Mean squared error (MSE) or mean squared deviation (MSD) of an estimator measures the average of the
squares of the errors or deviations
• Ie, the difference between the estimator and what is estimated.
• MSE is a risk function, corresponding to the expected value of the squared error loss or quadratic loss.
• The difference occurs because of randomness
• it is always non-negative, and values closer to zero are better.

25. FUTURESCOPE
• This proposed system can be further enhanced and made more secure by capturing the retinal image
of a person and performing the above mentioned encryption procedure to encrypt them and send over
a network.
• Also by combining more than one biometric attribute the security can be enhanced

26. CONCLUSION
• In our daily lives biometrics signal plays a vital role and the development and integration of biometric
authentication techniques used into practical applications increases nowadays.
• In this system , propose a biometrics-based authentication scheme using visual cryptography and
steganography Security .
• If the steganography scheme is alone applied it does not ensure secrecy when it was combined with a
blowfish encryption system and visual cryptographic technique it provides additional security.
• In this method the visual cryptographic share generation at the user registration phase and embedding
biometric signal to the video object at the login phase provide a secure authentication scheme .

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30. THANK YOU