Abstract
Prime numbers are fundamental to the most common type of asymmetric encryption used today, namely Diffie-Hellman key exchange, Rivest-Shamir-Adleman cryptosystems, ElGamal Cryptosystem, Elliptic curve cryptosystems, etc. The strength of primes lies in the fact that they are the ‘building blocks’ of mathematics and in addition there is infinity of them with no apparent regularity in their distribution. Given these characteristics, they were used to build efficient one way functions used in public key cryptography. This work aims at exploring sets of prime numbers with the objective of finding patterns in their structure. For this purpose an efficient supervised learning model called Support Vector Domain Description was used as an explorer. The experimental results have shown a good generalization capability of this model to describe new prime numbers.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
