ABSTRACT via various ways which is allowed


                In recent years, bank systems
are connected by the network technology all over the world. Core banking
network plays a vital role in transactions. Customers can be able to transfer
and receive money in their account via various ways which is allowed by the
banks. Payments are made by various methods such as demand draft, National
Electronic Fund Transfer(NEFT) payment system, Real Time Gross settlement(RTGS)
payment system and cheque. Cheque truncation system in bank clear the cheque  payment. It is useful for the employee to
clear the cheque from home branch to the clearing house of cheque branch.
During this case, cheque is scanned and the scanned image is transfer by the cheque
truncation system to clearing house of cheque branch through the communication
channel. Copyright protection and security for cheque image issue arises during
the transmission through the digital communication channel. To overcome this
issue, Discrete Wavelet Transform(DWT) – Singular Value Decomposition(SVD)
transform and RC4 Techniques with Chaotic Logistics Map (CLM) are used. It
helps the cheque image to facilitate digital image watermarking and provides
security for copyright protection. The strong key is provided by the Chaotic
Logistics Map function. The proposed work converts the initial value from the
key and this value is given as input for the CLM function then this generate
sequence of 256-bit key array. The final stage is the permutation process and
the result is get XORed with the plain image to produce the cipher image and
vice versa. The experimental results shows that the proposed work: (a) provides
the cipher image cannot be visually identified, (b) the statistical correlation
between the plain image and cipher image is eliminate, (c) very sensitive to
small changes in key, (d) provides no change in image during encryption and
decryption process, (e) robust to a wide range of attacks such as cropping
attack, Gaussian noise, JPEG compression attack, rotation attack, brightness
attack, contrast attack.

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                A digital
watermarking is a marker covertly embedded in a noise tolerant signal such as
text, image, audio, video. It is widely used for identifying ownership and
copyright protection of a image. In digital image watermarking, the digital
information of a watermark image is hidden in a carrier image but it does not
contain a information of a carrier image.  DWT-SVD provides robustness against various
attacks and the imperceptibility of hidden information. Digital watermarking
scheme is the combination of Discrete Wavelet Transform and Singular Value
Decomposition. The transformed image’s matrix decomposed into each level of
decomposition for two dimensional DWT. The decomposed matrices into four
frequencies such as LL, HL, LH and HH frequencies. The watermark image is
embedded in all of these frequencies leads to negative correlated and posses
negative film effect during the extraction process. In order to increase the
robustness by adding the singular values to HH frequency band in DWT. It is
highly sensitive to human visual system, which maintains the perceptual quality
of the watermarked image. Due to high development in network and communication
technology, there is a need for providing secure communication while exchanging
confidential information like image, audio and video. It can be achieved by
changing the shape of the transmitted image, which is called as encryption. In
this process, the image encrypted with the help of encryption algorithm and
secret key. In Wired Equivalent Privacy, the image is encrypted by using RC4
encryption algorithm. During the encryption process, long pseudorandom bits are
generated by the Chaotic Logistics Map function. It improves the confusion and
diffusion by the discrete exponential chaotic maps and it provides strong resistance
to brute force attack, statistic attack and differential attack. During the
transmission of cheque image intruders may attack the encrypted image. Hence it
can be evaluate by active and passive attack such as cropping attack, Gaussian
noise, JPEG compression attack, rotation attack, brightness attack, contrast