# A Finite State Machine-Based Improved Cryptographic Technique
## 4 Results and Analysis of Proposed Work  
The primary purpose of the recommended MCTC is to provide a shuffling pattern that is both surprising and completely at random. It is possible to evaluate how much unpredictability the MCTC really injects into its output by using several different randomization tests. In the SIPI Database, the miscellaneous volume consists of 44 images, 16 color and 28 monochrome. The sizes are 14 lots of 256 \(\times\) 256, 26 lots of 512 \(\times\) 512, and 4 lots of 1024 \(\times\) 1024. The randomness test is an empirical procedure that involves a set of tests designed to evaluate how random a certain sequence really is. The statistical characteristics of the random numbers that are generated may be checked, and several different statistical tests can be used to determine the extent to which those statistical qualities are met. The results of these tests indicate the presence of a pattern in the sequence. When a sequence displays a pattern, it is an unmistakable sign that the sequence is not random. This renders the sequence both predictable and susceptible to being targeted by an adversary. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{2}{c}{**Secret Lookup Table**} & \multicolumn{4}{c}{**Interleaved Bit location**} \\ \hline  & & \multicolumn{2}{c}{**Case 1**} & \multicolumn{2}{c}{**Case 2**} & \multicolumn{2}{c}{**Case 3**} \\  & & \multicolumn{2}{c}{\(P\) = (13,10)} & \multicolumn{2}{c}{\(P\) = (9,1)} & \multicolumn{2}{c}{\(P\) = (9,1)} \\  & \(k_{m}\) = 2,853,234 & \multicolumn{2}{c}{\(k_{s}\) = 129,865,731} & \(k_{s}\) = 129,865,731 & \(k_{s}\) = 129,865,732 \\ \hline \(i\) & \(xi\) & \(y\)\(j\) & \(t\) & \(t\) & \(t\) \\ \hline
1 & 0 & 2 & 1 & 0 & 1 \\
2 & 1 & 3 & 3 & 8 & 7 \\
3 & 0 & 4 & 4 & 4 & 5 \\
4 & 1 & 5 & 5 & 7 & 5 \\
5 & 0 & 6 & 6 & 5 & 2 \\
6 & 1 & 7 & 7 & 6 & 1 \\
7 & 1 & 10 & 8 & 9 & 4 \\
8 & 6 & 14 & 9 & 13 & 12 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Secret key lookup table. The amplitude, direction, and form of the link between the input and output may be seen with the use of an MCTC scatterplot. When looking at the correlation coefficient, a result that is high is indicative of an extraordinarily strong link. A pattern in which there is no obvious center and a practically null CC would be a great depiction of a random Finite State Machine (FSM). Dispersion, on the other hand, is a statistical metric that is used to evaluate how much of a stretch there is in a certain distribution. If the dispersion value is made higher, the locations of the bits that are interleaved will become more spread apart. NIST FIPS-140-2, the industry-standard statistical test suite, is used to provide further verification on the proposed MCTC's statistical characteristics. In the following, you will find a detailed explanation of the different examinations. A scatter plot may be used to illustrate the unpredictability of the output sequence. It is desirable for the scatter plot to contain points that are distributed in a way that is both random and consistent. If the scatter plot displays a pattern that can be predicted, the parameters that were used to construct the sequence may be uncovered, which would leave the cryptosystem vulnerable to attack. The bit locations in the input and the bit positions in the output have absolutely no link with one another, as is seen from the picture. Altering the values of \(k_{\mathrm{s}}\) also results in a striking transformation of the pattern. Because of this, the scatterplot ensures that the random numbers that are generated are one-of-a-kind for each user and are founded on the MCTC keys that they have. The link between the MCTC's input and output is one that is overly sensitive to the way its key is configured. An opponent who does not possess the relevant keys will be unable to discern the connection between the bits that are input and bits that are output because of this. This time, the test was conducted between two interleaved bit location sequences known as \(\mathrm{v_{i}}\) and \(\mathrm{v_{i+1}}\).