Detecting Encrypted and Unencrypted Network Data Using Entropy Analysis and Confidence Intervals.

The detection of clear and encrypted data that are transported through computer networks is of particular importance both for protecting the data and the users to whom they belong and to whom they are intended, as well as the networks through which they are transmitted. The proposed method consists of an algorithm that classifies the data it receives by testing the belongingness of their standard deviation values to established confidence intervals. Following the evaluation of the algorithm, an accuracy of 94.73% was obtained and it appears that the results can be used with certainty in subsequent analyses of the data detection.