View of Fibonacci Transform Algorithm for Encryption and Decryption of Covid Images

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Fibonacci Transform Algorithm for Encryption and Decryption of Covid Images

Habibulla Mohammad1

1*

_{, Ch Gangadhar}

2

_{, K Phani Rama Krishna}

3 1_{Prasad V.Potluri Siddhartha Institute of Technology, Kanuru}

2_{Prasad V.Potluri Siddhartha Institute of Technology, Kanuru} 3_{Prasad V.Potluri Siddhartha Institute of Technology, Kanuru}

honeyhabeeb@gmail.com1_{, gangadharch1111@gmail.com}2_{,kprkrishna007@gmail.com}3

Article History: Received: 10 January 2021; Revised: 12 February 2021; Accepted: 27 March 2021; Published

online: 20 April 2021

Abstract: Picture encryption is a powerful strategy to ensure pictures or recordings by moving them into unrecognizable

formats for various security purposes. In this paper, Fibonacci Algorithm for Covid pictures encryption and Discrete wavelet change based Orthogonal Frequency Division Multiplexing for transmission and gathering is proposed. This paper presents execution of Fibonacci Algorithm for picture encryption and Discrete wavelet change based Orthogonal Frequency Division Multiplexing handset utilizing Discrete wavelet transform using Field Programmable Gate Array.

Keywords : Fibonacci transform, cryptography, image encryption, image decryption, WOFDM, VLSI

1. Introduction

Solid interest in computerized signal preparing and picture handling has been found in improvements in correspondence innovation. On account of remote and general correspondence organizations, be that as it may, unapproved information access has become more straightforward and more widespread [1-5]. Clinical picture security is a significant issue when computerized pictures and their relevant patient data are sent across open organizations.

OFDM relies upon Orthogonality principle. Orthogonality implies that it makes sub-transporters that are symmetrical to one another, guaranteeing that cross-channel contact is stayed away from and there is no requirement for between transporter monitor groups.

Symmetrical Frequency Division Multiplexing (OFDM) is a technique for computerized multi transporter adjustment that utilizes an enormous number of symmetrical sub-transporters that are firmly divided. A solitary information stream is partitioned into equal streams, every one of which is coded and balanced on an OFDM gadget subcarrier [6].In practice, the Fast Fourier Transform calculation is utilized to produce and distinguish OFDM signals. As Fast Fourier Transformation (FFT) includes muddled equipment, symmetrical recurrence division multiplexing is more complex monitor groups.

Existing remote correspondence frameworks were created on the numerical ideas of Fourier change. Fourier change breaks down sign into rudimentary waveforms; however these premise capacities are sine and cosines. The wavelet change premise capacities are minimal as expected, while the Fourier sine and cosine capacities are most certainly not. The premise elements of wavelet change are confined as expected and recurrence, and offer diverse resolutions [7]. Wavelet premise capacities offer adaptability and adaption that can be custom fitted to fulfill requests of remote correspondence frameworks. The opportunity to modify the properties of wavelet change offers the chance to adjust and upgrade the regulated sign as per application prerequisites of remote correspondence frameworks. Later on remote correspondence organizations, there needs more recurrence asset for better correspondence. Wavelet change based frameworks can deftly control the impedance between adjoining subcarriers.

In this paper, Fibonacci Algorithm for picture encryption and discrete wavelet change based Orthogonal Frequency Division Multiplexing (WOFDM) for transmission is proposed to upgrade the security and execution

2. The Proposed Encryption and Decryption Fibonacci Transform algorithm

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

F

_p

(

i

−

1 )

+

F

_p

(

i

−

p

−

1 )

i



0

By applying condition (1) we fabricate Fibonacci arrangement which comprises of the numbers (0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144…) Fibonacci change can be effectively speak to as a 2*2 lattice by any four continuous terms of the Fibonacci numbers, this network can be seen as a cover use for picture scrambling. A summed up Fibonacci cover can be characterizing as

[x_ynew new] = [ fi fi+1 fi+2 fi+3 ] [ x y] [2]

Where x, y, 𝑥𝑛𝑒𝑤, 𝑦𝑛𝑒𝑤 ∈ 0, 1, 2, 3, 4….−1, is the ith term of the Fibonacci arrangement, and n is the size of the computerized squared picture and 𝑥𝑛𝑒𝑤 , 𝑦𝑛𝑒𝑤 is the new facilitate for the pixel in the mixed picture. This veil can examine the entire picture from left to right and top to down, which scramble the pixels to make new picture. Encryption Method is appeared in Figure 1 and Decryption technique is appeared in Figure 2

(a) Encryption method

(1) The information picture will be perused as a lattice X. For best outcome it is smarter to deal with the picture as square picture, for that the picture or the grid will be change to square framework (picture) in the event that it isn't square.

(2) Change the components of the lattice X haphazardly by utilizing Fibonacci Transform to get picture network Y

(b) Decryption method

Unique picture can be delivered by the converse of Fibonacci change on Y picture network.

The encoded picture is applied to wavelet change based Orthogonal Frequency Division Multiplexing (WOFDM) for transmission and got picture is decoded utilizing unscrambling calculation.

Figure1. Encryption Method

Fibonacci sequence Fibonacci transform Encrypted image Original image Fibonacci sequence Inverse Fibonacci Transform Encrypted image

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1507 Figure 2. Decryption Method

3. Implementation of Discrete Wavelet Transform (DWT) OFDM System

The DWT OFDM framework was demonstrated utilizing VHDL and executed utilizing FPGA is appeared in Figure 3. A concise depiction of the model is given underneath.

Figure. 3 Arrangement for a DWT OFDM transmitter and recipient

Discrete wavelet change can be utilized as a reversible and lossless change. The following are the conditions for forward and reverse wavelets change.

i) Forward Discrete Wavelet transform

(2 )

(2

2)

(2

1)

(2

1)

2 x

n

x

n

y

n

+ =

x

n

+ − 



+

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_





_[3]

(2

1)

(2

1)

2 (2 )

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4 y

n

y

n

y

n

=

x

n

+ 



− +

+ +

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_

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_[4]

ii) Inverse Discrete Wavelet Transform:

(2

1)

(2

1)

2 (2 )

(2 )

4 y

n

y

n

x

n

=

y

n

− 



− +

+ +



_





_[5] [6]

VLSI engineering of wavelet change is delineated in the figure 4 and figure 5

Figure. 4 Design of Discrete wavelet change

(2 )

(2

2)

(2

1)

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1)

2 x n

x n

+ =

y

n

+ + 

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

_





Y(2n) Y(2n+1) + X(2n) X(2n+1) + X(n)

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1508 Figure. 5 Design of Inverse Discrete wavelet transforms

4. Results

We planned our Fibonacci change encryption, unscrambling and DWT OFDM utilizing VHDL and executed rationale re-enactment with the utilization of XILINXISE and ModelSim.

First Covid picture information appeared in Figure.6 and Encrypted picture is appeared in figure 7. Encoded picture is sent through discrete wavelet change based OFDM and got picture is appeared in figure8. Second Covid picture information appeared in Figure.9 and Encrypted picture is appeared in figure 10. Encoded picture is communicated through discrete wavelet change based OFDM and got picture is appeared in figure11.

. Figure 6.First Covid image (01BA-7J04C)

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1509 Figure7.First Covid encrypted image

Figure8.Received first Covid image (01BA-7J04C)

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1510 Figure10.Second Covid Encrypted image (01BA-7HDQ)

Figure11. Received Second Covid image (01BA-7HDQ)

Asset rundown used to actualize the Fibonacci change encryption and discrete wavelet change based OFDM utilizing FPGA utilizing Xilinx ISE are shown in Table1.

Table 1. FPGA Device (Kintex) utilization summary

S.No. Slice Logic Utilization

1 Number of Slice LUTs

73125 out of 712000

Timing Summary: Maximum frequency of clock=49MHZ

5. Conclusion

In this paper, Fibonacci change and discrete wavelet change based OFDM transmitter and beneficiary is proposed and actualized utilizing FPGA .The viability of the VLSI engineering intended for the proposed calculation is shown through usage on a Covid picture utilizing XILINXISE and ModelSim.

6. Acknowledgement

The authors would like to thank PVP Siddhartha Institute of Technology. This research is supported by Research and Development cell, Electronics and Communication Engineering Department.

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A.

Grangetto, M., Magli, E., & Olmo, G. (2006). Multimedia Selective Encryption by Means of Randomized

Arithmetic Coding. IEEE Transactions on Multimedia, 8(5), 905–917.

https://doi.org/10.1109/tmm.2006.879919.

B.

Masuda, N., & Aihara, K. (2002). Cryptosystems with discretized chaotic maps. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 49(1), 28–40. https://doi.org/10.1109/81.974872.

C.

Lautenbach, B. (2004). Introduction to XML Encryption and XML Signature. Information Security Technical Report, 9(3), 6–18. https://doi.org/10.1016/s1363-4127(04)00028-7

D.

Fu, C., Lin, B.-, Miao, Y.-, Liu, X., & Chen, J.-. (2011). A novel chaos-based bit-level permutation scheme for digital image encryption. Optics Communications, 284(23), 5415–5423. https://doi.org/10.1016/j.optcom.2011.08.013

E.

Ye, G., & Huang, X. (2016). A secure image encryption algorithm based on chaotic maps and SHA-3. Security and Communication Networks, n/a. https://doi.org/10.1002/sec.1458

F.

Wei-Hsin Chang, & Truong Nguyen. (2006). An OFDM-specified lossless FFT architecture. IEEE Transactions on Circuits and Systems I: Regular Papers, 53(6), 1235–1243. https://doi.org/10.1109/tcsi.2006.875167

G.

Liu, Z., Chiew, K., Zhang, L., Zhang, B., He, Q., & Zimmermann, R. (2016). Rare category exploration via wavelet analysis: Theory and applications. Expert Systems with Applications, 63, 173–186. https://doi.org/10.1016/j.eswa.2016.06.033