Modelling
We modelled several aspects of the CryptoGErM system. These models are described and explained in detail in the following articles:
Belief-Desire-Intention
The AI model explores the behaviour of the people who use, or try to abuse,
the CryptoGErM system. The people are modelled in a multi-agent simulation using genetic algorithms.
This model helps us to predict the
and intentions of the users and intruders of our system.
Random mutations in Bacillus subtilis
The data stored in the CryptoGErM system
might be endangered by random mutations in the DNA.
This article contains research of the literature on known mutation rates of Bacillus
under the special conditions and treatments that will be applied.
Random mutations modelling
In this section we computationally modelled
the probaility of random mutation causing our message in the DNA to be corrupted.
Decoding fidelity
In the decoding fidelity section we explore how accurate the current sequencing techniques
are and how strong our decoy encryption security layer is.
Searching for an optimal strain
We modelled the protein-DNA interactions in oder to search for an optimal strain
for our photoswitchable antibiotic experiments.
