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A Review on "Locating Secret Images Using DWT Techniques and RSA Algorithm"

Authors:
Jyoti Chaudhary at The Technological Institute of Textile and Sciences Bhiwani (Haryana)
Jyoti Chaudhary
  • The Technological Institute of Textile and Sciences Bhiwani (Haryana)
Sneha
Sneha
Sneha
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Abstract

Steganography is the science that involves communicating secret data in an appropriate multimedia carrier like image, video and audio files. it does not replace cryptography but rather boots the security using its obscurity features. When we work on a network the security requirements of a user as well as a network increases. There are number of available ways over the network to achieve the information security. Till now the available methods hide the secret data over the image on a fixed pattern that makes a user identify the pattern easily. We are providing a dynamic pattern extraction approach using biometric. It advocates an object-oriented approach in which skin tone detected areas in the image are selected for embedding where possible. After detecting the skin area, edge detection is performed by using the canny edge detection method. As the edges will be detected we will use this area as the pattern to hide the data over the image. The secret data is compressed using the DWT technique and then further compressed secret information is encrypted using RSA algorithm with bit shift method. This proposed technique provides more security to the data as data is embedded not in the whole image but only at some specified location. Due to this image distortion of the carrier image is less and it is difficult to identify the Secret image.
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ISSN(Online): 2320-9801
ISSN (Print) : 2320-
9798
International Journal of Innovative Research in Computer
and Communication Engineering
(An ISO 3297: 2007 Certified Organization)
Vol. 4, Issue 5, May 2016
Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0405321 9633
A Review on "Locating Secret Images Using DWT
Techniques and RSA Algorithm"
Sneha, Jyoti
M.Tech Scholar, Dept. of CSE, Technological Institute of Textile & Sciences, Bhiwani, Haryana, India
Asst. Professor, Dept. of IT, Technological Institute of Textile & Sciences, Bhiwani, Haryana, India
ABSTRACT: Steganography is the science that involves communicating secret data in an appropriate multimedia
carrier like image, video and audio files. it does not replace cryptography but rather boots the security using its
obscurity features. When we work on a network the security requirements of a user as well as a network increases.
There are number of available ways over the network to achieve the information security. Till now the available
methods hide the secret data over the image on a fixed pattern that makes a user identify the pattern easily. We are
providing a dynamic pattern extraction approach using biometric. It advocates an object oriented approach in which
skin to ne detected areas in the image are selected for embedding where possible. After detecting the skin area, edge
detection is performed by using the canny edge detection method. As the edges will be detected we will use this area as
the pattern to hide the data over the image. The secret data is compressed using the DWT technique and then further
compressed secret information is encrypted using RSA algorithm with bit shift method. This proposed technique
provides more security to the data as data is embedded not in the whole image but only at some specified location. Due
to this image distortion of the carrier image is less and it is difficult to identify the Secret image.
KEYWORDS: secret data, rsa, edge detection, DWT
I. INTRODUCTION
A. Steganography
The word Steganography is originally derived from Greek words which mean “Covered Writing”. Steganography is a
technique that embedding the secret information into an another image so that unknown user cannot identify that secret
information. Steganography is the skills of writing secrete messages in such a way that no one, other than the sender
and receiver, suspects the survival of the message, a form of security through obscurity
B. Cryptography
Cryptography is the science of using mathematics to encrypt and decrypt data. The word cryptography is derived from
the Greek word kryptos, meaning ’hidden’. Cryptography enables us to store sensitive information or transmit it across
insecure networks (like the Internet) so that it cannot be read by anyone except the intended recipient.
II. PROPOSED ALGORITHM
Step 1: Cover image is loaded & skin color detection is performed for the biometric image.
Step 2: Apply canny edge detector algorithm for the biometric image.
Step 3: Once the edges of cover image are found then load the secret image.
Step 4: After loading the secret image, DWT technique is applied to compress the secret image as
compressed image will less distort the cover image.
Step 5: Then RSA encryption algorithm with bit shift method is performed.
Step 6: Encrypted message is then embed behind the cover image.
Step 7: Stego image with better quality is obtained.
ISSN(Online): 2320-9801
ISSN (Print) : 2320-
9798
International Journal of Innovative Research in Computer
and Communication Engineering
(An ISO 3297: 2007 Certified Organization)
Vol. 4, Issue 5, May 2016
Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0405321 9634
III. RSA ALGORITM WITH BIT SHIFT METHOD
There are various steps to implement RSA algorithm:
1. Choose two large prime numbers p, q randomly.
2. Compute n = pq.
3. Calculate φ(n) as follow:
φ(n) = (p-1)(q-1)
4. Choose an integer e such that e is relatively prime to φ(n).
1 < e < φ(n)
such that
gcd (φ(n),e) =1
5. Determine d, 1 < d < φ, such that
d = e-1(mod(φ(n)))
6. Encryption:
Plaintext M < n
Ciphertext C=Me mod n
7. After the encryption bit shift method is used where left four bits of a byte are XOR with the right four bits
and resultant bits are set at the place of right 4 bits.
8. Decryption:
Ciphertext C
Plaintext M=Cd mod n
IV. FLOWCHART
The flowchart shows that first the cover image is loaded and then skin tone detection is done when the cover image is
biometric and if the image is non-biometric then edge detection algorithm is applied. After that the secret image is
loaded and DWT method is applied to it which will give compressed secret image. Then this image is encrypted by
using the RSA with bit shift method. Encrypted image is then embed into the edge pixels of the cover image. This
method of data hiding is more secure as secret image only uses the edge pixels and data is not dispersed in the whole
cover image. As distortion of cover image is less and then the image quality of stego image is good.
ISSN(Online): 2320-9801
ISSN (Print) : 2320-
9798
International Journal of Innovative Research in Computer
and Communication Engineering
(An ISO 3297: 2007 Certified Organization)
Vol. 4, Issue 5, May 2016
Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0405321 9635
V. CONCLUSION
As Steganography is concerned with security purpose and it is consider as a fascinating scientific area .the proposed
algorithm pre processes the data before hiding it behind the cover image. the compression step involved in the
algorithm reduces the size of text and thus allows more data to be hidden behind the same image. so, using compression
more data can be hidden acknowledgment behind the same image. The skin area and the edge pixels are evaluated and
secret data which is encrypted with RSA algorithm is embedded into specific area .As data is embedded in certain
region rather than whole image so security as well as quality of stego image is enhanced. The data is hidden only in the
edge pixels of cover image which is least imperceptible to human eye thus providing a higher PSNR value and no
visual distortion of image quality. Moreover, the size of the image does not change after hiding the text in it.
VI. ACKNOWLEDGEMENT
It is great opportunity to write about “Locating Secret Images Using DWT Techniques and RSA Algorithm”. For
preparing this paper I am gone through different books and websites to understand this topic easily.
I acknowledge with gratitude to Astt professor JYOTI CHOUDHRY who has always been sincere and helpful in
making me understand this research.
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ResearchGate has not been able to resolve any citations for this publication.
A Comparative Study of ±1 Steganalyzers
Conference Paper
Full-text available
  • Oct 2008
We compare the performance of three steganalysis system for detection of plus/minus 1 steganography. We examine the relative performance of each system on three commonly used image databases. Experimental results clearly demonstrate that both absolute and relative performance of all three algorithms vary considerably across databases. This sensitivity suggests that considerably more work is needed to develop databases that are more representative of diverse imagery. In addition, we investigate how performance varies based on a variety of training and testing assumptions, specifically (i) that training and testing are performed for a fixed and known embedding rate, (ii) training is performed at one embedding rate, but testing is over a range of embedding rates, (iii) training and testing are performed over a range of embedding rates. As expected, experimental results show that performance under (ii) and (iii) is inferior to (i). The experimental results also suggest that test results for different embedding rates should not be consolidated into a single score, but rather reported separately. Otherwise, good performance at high embedding rates may mask poor performance at low embedding rates.
View
Securing information content using new encryption method and Steganography
Conference Paper
Full-text available
  • Nov 2008
This paper proposes a novel encryption method with password protection based on an extended version of SHA-1 (secure hash algorithm) that is able to encrypt 2D bulk data such as images. There has been a modest research in the literature on encryption of digital images though. The algorithm benefits also from the conjugate symmetry exhibited in what is termed, herein, an irreversible fast Fourier transform (IrFFT). The proposed encryption method is a preprocessing phase which aims at increasing the robustness of image steganography against hackers. This scenario lays down a multi layer of security which forms a strong shield, against eavesdroppers, that is impossible to break. Both Shannon law requirements are met and results show promising results.
View
A steganographic method based upon JPEG and quantization table modification
Article
  • Mar 2002
  • INFORM SCIENCES
In this paper, a novel steganographic method based on joint photographic expert-group (JPEG) is proposed. The proposed method modifies the quantization table first. Next, the secret message is hidden in the cover-image with its middle-frequency of the quantized DCT coefficients modified. Finally, a JPEG stego-image is generated. JPEG is a standard image and popularly used in Internet. The stego-image will not be suspected if we could apply a JPEG image to data hiding. We compare our method with a JPEG hiding-tool Jpeg–Jsteg. From the experimental results, we obtain that the proposed method has a larger message capacity than Jpeg–Jsteg, and the quality of the stego-images of the proposed method is acceptable. Besides, our method has the same security level as Jpeg–Jsteg.
View
View
Skin Segmentation Using Color Distance Map and Water-Flow Property
Conference Paper
  • Oct 2008
A new approach for skin region segmentation is proposed. It uses color distance map (CDM) and an algorithm based on the property of flow of water. The CDM itself is a grayscale image, which makes the algorithm very simple. However, it is still capable of providing color information based on which some skin and non-skin seed regions can be determined reliably. Then a water-flow based procedure determines skin and non-skin segments completely. The color distance map is robust against variations in imaging conditions and the water-flow procedure efficiently uses the region information to extract solid skin segments without generating much noisy segments.
View
Robust data hiding for images
Conference Paper
  • Feb 2000
This paper describes a robust data embedding scheme, which uses a source and channel coding framework for data hiding. The data to be embedded, referred to as the signature data, is source coded by vector quantization and the indices obtained in the process are embedded in the wavelet transform coefficients of the host image. Transform coefficients of the host are grouped into vectors and perturbed using error-correcting codes derived from BCH codes. Compared to prior work in digital watermarking, the proposed scheme can handle a significantly large quantity of data such as a gray scale image. A trade-off between the quantity of hidden data and the quality of the watermarked image is achieved by varying the number of quantization levels for the signature, the codeword length, and the scale factor for embedding. Experimental results on signature recovery from JPEG compressed watermarked images are included
View
Pixel-based skin detection for pornography filtering
  • Jan 2005
  • 21-41
  • A Abadpour
  • S Kasaei
Abadpour, A. & Kasaei, S., 2005. Pixel-based skin detection for pornography filtering. Iranian Journal of Electrical and Electronic Engineering, 1(3), pp.21-41.
A discrete Wavelet transform based technique for image data hiding
  • Jan 1920
  • 1-9
  • A A Abdelwahab
  • L A Hassan
Abdelwahab, A.A. & Hassan, L.A., 2008. A discrete Wavelet transform based technique for image data hiding. In Proceedings of 25th National Radio Science Conference, NRSC 2008. Egypt, 2008. March 18-20.pp.1-9.
Exploiting preserved statistics for steganalysis
  • May 2005
  • Lect Notes Comput Sci
  • 82-96
  • R Böhme
  • A Westfeld
Böhme, R. & Westfeld, A., 2005. Exploiting preserved statistics for steganalysis. In Proceedings of 6th International Workshop Information Hiding. Toronto, Canada, 2005 Lecture Notes in Computer Science, Springer. 23-25 May. pp.82-96.
Matlab Implementation of the Advanced Encryption Standard
  • Jan 2001
  • R Bourdon
Bourdon, R., 2009. WampServer. [Online] Availablat: HYPERLINK"http://www.wampserver.com/en/" http://www.wampserver.com/en/ [Accessed 04 August 2009]. Buchholz, J.J., 2001. Matlab Implementation of the Advanced Encryption Standard.http://buchholz.hsbremen.de/aes/aes.htm.