To propose an image encryption system using one dimensional cellular automata for image encryption and decryption. Cellular automata can be corresponded with the essential cryptographic properties i.e. Balance, correlation-immune, nonlinearity, easy to implement in hardware. CA cryptosystems can give better performances compared to classic methods that are based on computational techniques. Therefore, this technique should be most favourable for cryptography.

**Features:**

**1. Encryption –**

**RGB:**Extract individual RGB channel to encrypt each layer and merge.**Gray:**Convert the given image to grayscale and use it for encryption.

**2. Decryption –**

**Key:**Use a key for each pixel for decryption process stored in a separate file.**Preset:**Use predefined rules to decrypt the image.

**3. Result and Analysis –**

**Histogram:**Histogram analysis is defined as the frequency of the image pixels in graphical representation.**Correlation:**Correlation is a statistical measure that indicates the extent to which two or more variables fluctuate together.

**4. Rule Selection –**

Rules to be applied to encrypt image can be selected and order can be changed (R30, R90, R120).Further rules can also be added.

**Implementation/Algorithms:**

**Encryption –**

Converting image to 2d matrix and modifying each pixel value by using key function.- Grayscale image is taken as input.
- Image is converted to a 2D matrix (M).
- Execute M1=Key (M), where M1 is the encrypted 2D matrix.
- Each pixel values of M matrix is modified by using the Key function h1(M) depending on whether the value of the pixel sent is odd or even which is stored in a separate index file INF for each pixel.
- The modified pixel is then received and stored in M1.
- Matrix M1 is converted to image and saved as an encrypted image.

**Decryption –**

Original pixels are retrieved by using the reverse technique- Encrypted image is taken as an input
- Image is converted to a 2D matrix(M1).
- M=Key(M1) is executed, where M is the decrypted 2D matrix.
- Each pixel values of M1 matrix is modified by using the Key function h1(M) using its corresponding odd/even rule from index file INF.
- The modified pixel is then received and stored in M1.
- The M matrix is converted to image and saved as decrypted image.

**Key Function –**

Here a 2D matrix is taken as an input and this key () function is called during encryption as well as decryption which modifies the input pixel value using cellular automata rule vector.- The input pixel is converted into binary number of 8 blocks.
- Distinct cellular automata rules are applied per block.
- If input value is even, rule 90 and 30 are applied alternatively.
- If input value is odd, rule 90 is applied.
- The rule configuration is run till the initial input block repeats itself.
- Recursion stage is noted and half of that cycle is calculated hc = n/2.
- The rules are run once again but this time for half the cycle (hc).
- Final output of the array is converted back to decimal number and placed in the encrypted /decrypted value of the input block.
- Step 1 to step 7 is repeated until all the grayscale values are encrypted /decrypted.

**Tools:**

This image encryption system has been prepared on Python and MATLAB.

Following libraries are used:

OpenCV:To extract image pixels and modify it.Numpy:To make use of arrays in key function.Matplotlib:To obtain results (histogram, correlation)

Following Cellular Automata rules have been applied:

Rule 90 Rule 30 Rule 120

The whole program is divided into modules:

Encryption Script Decryption Script Result and Analysis

**Application –**

Image encryption is the primary task of the program I developed although the system proposed is not only limited to Image encryption. The system can be modified to achieve:

- Coding messages
- Picture compression
- Production of pseudo-random numbers.

**Project Link:**

https://github.com/Lakshyasukhralia/CellularAutomata

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