From Table 1, we can observe that the value of the private key must be higher
when the number of characters is increased to assure the original message be
recovered. We can see that for some values of private key the recovering fails.
Associative models have been applied in classification, prediction, pattern recognition
and feature selection. In this paper we demonstrated that this approach can also be
applied in text encryption.
The algorithm is symmetric and it has a private key.
The original massage is recovered always: the number of characters is not a
limitation; however, the value of the private key must be increased if the number of
characters in the message is increased too.
Acknowledgments. The authors would like to thank the Instituto Politécnico
Nacional (COFAA, SIP and EDI), and SNI for their economic support to develop this
work. Ángel Martínez is grantee PIFI.
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