This paper discusses implementation of Gauss-Circle Map (GCM) in cryptography and steganography process simultaneously. Cryptography is used for securing data confidentiality, while steganography is used to protect the existence of data. The objects that used in this thesis are digital text and digital images. This research was conducted by designing algorithms for encryption and embedding simultaneously, as well as extraction and decryption simultaneously then implement it with python programming. Results obtained from the observation shows that GCM had randomness level 100% using NIST test with chosen parameter x 0(1) = x 0(2) = 0, a (1) = a (2) = 9, ß (1) = ß (2) = 0.481, K (1) = K (2) = 1000000, and O(1) = O(2) = 0.5. Algorithm that have been designed have varying degrees of sensitivity according to different parameters, and high key spaces that reaches 2.6244 × 101269. Encrypted image is uniformly distributed since it passes goodness of fit test. Correlation coefficient values of the stego image are at interval [0.89,1] and very close to correlation coefficient values of the cover image. However, Peak Signal to Noise Ratio (PSNR) of the stego image did not meet standard (above 40 dB). Here, the extracted-decrypted stego image have perfect similarity with the original image.
|Journal||Journal of Physics: Conference Series|
|Publication status||Published - 29 Mar 2021|
|Event||6th International Conference on Mathematics: Pure, Applied and Computation, ICOMPAC 2020 - Surabaya, Virtual, Indonesia|
Duration: 24 Oct 2020 → …