A neural cryptography approach for digital image security using Vigenère cipher and tree parity machine
Mohammad Andri Budiman, Handrizal Handrizal, William William · Journal of Physics Conference Series · 2021
Abstract As with other form of digital media, image can also contain private information that should be kept secret. Commonly, symmetric and asymmetric cryptosystem can be used to secure an image. Symmetric-key cryptography is not a best solution as the secret key has to be transmitted through private channel. Asymmetric-key cryptosystem, however, allows transmission of key through public channel, but requires high computational power and long computational time. This paper proposes a neural cryptography approach to protect image by using tree parity machine and Vigenère cipher. By using this approach, the secret key will never be transmitted. Moreover, the whole process does not require high computational power and long computational time as in public-key cryptosystem. To overcome the weakness of Vigenère cipher, change is made to the algorithm by multiplying the key value with y-axis of image. The effectiveness is validated by the value of pearson correlation that is close to 0. Lastly, the result of experiments show neural synchronization time depends on the size of network, initial weights and randomly generated input vector.