## 4 Discussions  
Applying entropy compression before the transmission is a common daily practice. For instance, the _mpeg4_ encoded video streams, _jpg_ images, or text resources encoded with arithmetic or Huffman schemes are possible data sources fit well to the proposed architecture with their high entropy. It is noteworthy that the security of the high-entropy data has been previously addressed in [24; 25; 26]. These studies mainly state that although the perfect security of an input data requires a key length equal to its size (one-time pad), the security of high-entropy data can be provided with much shorter key sequences. However, again the data as a whole should be fed into encryption. On the other hand, high entropy data representation with our proposal creates two elements, where encrypting one of them is adequate since decoding the original data from the plain element is hard in absence of the other encrypted element. A recursive application of the proposed coding can even reduce the to-be-encrypted volume more. For example, after creating the two elements of the non-UD representation, the disambiguation information or the payload can itself be subject to a one more round of NPF coding. We have shown that when \(d=8\), \(\approx\) 25 percent is the disambiguation information, and with one more round, the disambiguation information will become less then 7 percent of the final volume, where encrypting only that 7% can be considered for privacy. A similar scenario on the payload can be considered as well. We assumed that the input to the non-UD encoder is uniformly i.i.d. in ideal case, and empirically verified that the compressed volumes ensures the mentioned results. Actually, applying entropy coding before the encryption is a common daily practice, which makes the proposed method to be directly applicable in such a scenario. The _mpeg4_ video streams, _jpg_ images, compressed text sequences, or _mp3_ songs are all typical data sources of high-entropy. Digital delivery of such multi-media content has a significant market share in daily practice [27]. Related previous work [24; 25] had stated that although the perfect security of an input data requires a key length equal to its size (one-time pad), high-entropy data can be perfectly secured with much shorter keys. This study addressed another dimension and investigated achieving security of such volumes by encrypting less than their original sizes by using the introduced non-UD coding scheme. Although we target high-entropy data and analyze space consumption and security features based on the assumption of i.i.d input, it might be also interesting to have a look what would happen if we apply the non-UD coding to normal files with biased distributions. On the corpus we studied, we omitted the compression step on the files that have non-uniform symbol distributions, and applied our proposed coding directly with a randomly selected \(\Sigma\to W\) mapping. The results are given on Table 5, where repeating the same experiment with different \(\Sigma\to W\) assignments reported similar values. The empirical observation on these results show that the disambiguation information is roughly less than one third of the input volume, when the input sequence is not uniformly distributed. Thus, encrypting only the disambiguation information may make sense still on non i.i.d files as well. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**File Name** & **File Size** & **Payload Size** & **Disinfo. Size** \\ \hline etext & 100.4 & 76.4 & 28.8 \\ howto & 37.6 & 30.1 & 9.3 \\ rctail96 & 109.4 & 84.7 & 29.9 \\ rfc & 111.1 & 87.4 & 29.1 \\ w3c2 & 99.3 & 77.1 & 27.2 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The sizes of the payload and disambiguation information when non-UD coding is applied on the files that have non-uniform symbol distribution. Reducing the amount of data to-be-encrypted can make sense in scenarios where the encryption process defines a bottleneck in terms of some metrics.