# DNA-PRESENT: An Improved Security and Low-Latency, Lightweight Cryptographic Solution for IoT
## 4 Security, Cost, and Performance Analysis
### Security Analysis
Here, AE is the avalanche effect; _ith_ plaintext and the ciphertext bits are represented as \(p_{i}\) and \(c_{i}\), respectively [73]. The value \"R\" derived from the test spans from \(-1\) to \(+1\), indicating the correlation between plaintext and ciphertext, summarized in Table 7. The value \"R = 0\" is ideal, as plaintext and ciphertext are independent of each other, and an attacker cannot establish any relationship between them by analyzing any given one. On a larger scale, the absolute values reveal the strength of  
Figure 17: Graphical representation of plaintext sensitivity test results (**a–i**). the relationship--where the smaller the number, the weaker the relationship--aligning with the intended goal of cryptographic algorithms. To validate this relationship, a dataset of 1000 random plaintexts was subjected to three key categories, ranging from RK, LDK, to HDK. For the test, a total of 15,000 values were observed, and the distribution of observations across each category is summarized in Table 8. For all other scenarios, the values are very close; however, there is an increase of 0.22% for R = 0 using DNA-PRESENT, highlighting a larger number of observations where no relationship can be established between the plaintext and ciphertext by the attacker. There is a decrease in weak negative relations with 0.5. These findings suggest that the enhanced algorithm has successfully reduced the linear relationship in fewer rounds, thereby concealing more information about the plaintext when presented with the ciphertext. This also endorses that the improved and original PRESENT are secure against ciphertext attacks. The exact values are depicted in graphs as Figure 18a-e for RK, Figure 18f-j for LDK, and Figure 18k-o for HDK values. \[R=\frac{\sum_{(i=1)}^{s}(p_{i}-AE)(c_{i}-AE)}{\sqrt{\sum_{(i=1)}^{s}(p_{i}-AE)^ {2}}\sqrt{\sum_{(i=1)  
test measures the relationship between plaintext and ciphertext. As a mathematical expression, this BER can be expressed as Equation (5):  
\[BER=\frac{Number\ of\ cipher\ bit\ difference}{Total\ number\ of\ ciphertext\ bits} \tag{5}\]  
Three different datasets of plaintext are compared for BER against HDK. Individual values of each dataset are presented in Table 9. On average, the original technique has a bit difference of 31 bits, whereas DNA-PRESENT consistently achieved a 32-bit difference, which accurately reflects a 50% error rate. A pictorial representation of all the observations for the three scenarios mentioned above is presented in Figure 19. The number of plaintext bits modified for each observation is indicated on the X-axis, and the Y-axis contains the bit error rate (BER) values. \begin{table}
\begin{tabular}{l l l l l l l l l l} \hline \hline  & \multicolumn{4}{c}{**DNA-PRESENT**} & \multicolumn{4}{c}{**PRESENT**} \\ \hline
**Input** & **Average Different Bits** & **Average BER** & **Average Different Bits** & **Average BER** \\ \hline RP & 32.125 & 0.501953125 & 31.28125 & 0.488769531 \\ HDP & 32.140625 & 0.502197266 & 31.609375 & 0.493896484 \\ LDP & 32.140625 & 0.502197266 & 30.65625 & 0.479003906 \\ \hline Avg & 32.135 & 0.50211588 & 31.1822 & 0.4872233 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: BER comparison of DNA-PRESENT and PRESENT. \begin{table}
\begin{tabular}{l l l l l l l l l l l l} \hline \hline  & \multicolumn{4}{c}{**DNA-PRESENT**} & \multicolumn{4}{c}{**PRESENT**} \\ \hline
**Key** & **Prised** & **Prised** & **Prised** & **Prised** & **Prised** & **Prised** & **Prised** & **Prised** & **Prised** & **Prised** \\  & **Prised** & **Prised** & **Prised** & **Prised** & **Prised** & **  
Figure 19: Graphical representation of bit error rate test results (**a**–**c**). Figure 18: Graphical representation of correlation coefficient test results (**a**–**l**).