Best Fit DNA-Based Cryptographic Keys: The Genetic Algorithm Approach.

Area of Science:

• Computer Science
• Cryptography
• Bioinformatics

Background:

• DNA cryptography encodes information using DNA sequences, relying on robust cryptographic keys.
• Weak keys in DNA cryptography, due to redundancy, are vulnerable to security breaches.
• Existing methods may discard weak keys, leading to potential loss of valuable cryptographic resources.

Purpose of the Study:

• To propose a novel Genetic Algorithm-inspired method for strengthening weak DNA cryptographic keys.
• To enhance the security and resilience of DNA-based information encoding schemes.
• To optimize the utilization of keys generated by Random DNA-based Key Generators.

Main Methods:

• A Genetic Algorithm approach is adapted for DNA cryptography, modifying fitness functions and genetic operators.
• Crossover and mutation rates are dynamically adjusted across successive populations.
• Key population size is increased to create a more exhaustive key space, deterring brute-force attacks.

Main Results:

• The proposed method successfully strengthens weak DNA keys, reducing their vulnerability.
• Demonstrated that an initial population of 25x25 DNA keys yielded 14 weak keys, all strengthened within 4 new populations.
• Analysis indicates a maximum of 8 new populations are needed to strengthen 500 weak keys from a 500x500 initial population.

Conclusions:

• The Genetic Algorithm-inspired method effectively strengthens weak DNA cryptographic keys without discarding them.
• The approach enhances the overall security of DNA cryptography against various intrusion methods.
• The study confirms the scalability and efficiency of the proposed key strengthening technique for large key populations.