https://github.com/eddieoz/rsa-primes-resolution

Recover a Private Key from a given Public Key using the Right Triangle-based Constant time mathematical solution method.
https://github.com/eddieoz/rsa-primes-resolution

decryption encryption encryption-decryption keras keras-neural-networks neural-networks private private-key-cryptography public-key-cryptography rsa rsa-algorithm rsa-cryptography rsa-decryption rsa-encryption rsa-key-encryption

Last synced: 4 days ago
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Recover a Private Key from a given Public Key using the Right Triangle-based Constant time mathematical solution method.

• Host: GitHub
• URL: https://github.com/eddieoz/rsa-primes-resolution
• Owner: eddieoz
• License: mit
• Created: 2020-12-29T17:43:38.000Z (almost 4 years ago)
• Default Branch: master
• Last Pushed: 2024-09-09T08:41:03.000Z (about 2 months ago)
• Last Synced: 2024-10-24T21:31:49.191Z (13 days ago)
• Topics: decryption, encryption, encryption-decryption, keras, keras-neural-networks, neural-networks, private, private-key-cryptography, public-key-cryptography, rsa, rsa-algorithm, rsa-cryptography, rsa-decryption, rsa-encryption, rsa-key-encryption
• Language: Python
• Homepage:
• Size: 15.6 KB
• Stars: 10
• Watchers: 3
• Forks: 3
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# RSA-primes-resolution

- Reconstruct a Private Key from a given Public Key using the Right Triangle-based Constant time mathematical solution method (find_primes.py) and by using Neural Networks with Keras (find_primes-nn.py). 

# Security Considerations

- This tool was developed for educational and research purposes, it must not be used to compromise the security of real systems without express authorization. The effectiveness of the tool depends on the size of the RSA keys and the training quality of the neural network model.

# Future Improvements

- [ ]  Implement a data collection and storage system to continually improve the neural network model.

- [ ]  Optimize the algorithm to handle larger RSA key sizes.

- [ ]  Implement parallel processing to improve performance on multi-core hardware.

- [ ]  Develop a user-friendly interface to facilitate use by non-experts.