Encryption function on artificial neural network
Six algorithms that design secrecy keys are used for digital image encryption. The privacy keys generated by stream cipher generators were tested for their randomness applying five tests of randomness. The images generated by applying each algorithm were tested for their regularity and residual inte...
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| Format: | Article |
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Springer Verlag (Germany)
2016
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| _version_ | 1825721064365228032 |
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| author | Al Azawee, H. Husien, S. Yunus, M.A.M. |
| author_facet | Al Azawee, H. Husien, S. Yunus, M.A.M. |
| author_sort | Al Azawee, H. |
| collection | UM |
| description | Six algorithms that design secrecy keys are used for digital image encryption. The privacy keys generated by stream cipher generators were tested for their randomness applying five tests of randomness. The images generated by applying each algorithm were tested for their regularity and residual intelligibility. The histograms for images ciphered by stream cipher schemes all have approximately flat histogram less information as compared to one-dimensional ciphering algorithms and threshold generator-based image ciphering scheme. Furthermore, the stream cipher schemes were effectively applied to the colored images of 256-color levels of true-color images (24 bit). In this paper, we try to decrypt automatically using artificial neural network by decryption through multilayer perceptron and radial basis function; networks were tested using the interface by calculating the error rates of decrypted images. |
| first_indexed | 2024-03-06T05:44:39Z |
| format | Article |
| id | um.eprints-18176 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:44:39Z |
| publishDate | 2016 |
| publisher | Springer Verlag (Germany) |
| record_format | dspace |
| spelling | um.eprints-181762017-11-09T01:18:59Z http://eprints.um.edu.my/18176/ Encryption function on artificial neural network Al Azawee, H. Husien, S. Yunus, M.A.M. QA75 Electronic computers. Computer science Six algorithms that design secrecy keys are used for digital image encryption. The privacy keys generated by stream cipher generators were tested for their randomness applying five tests of randomness. The images generated by applying each algorithm were tested for their regularity and residual intelligibility. The histograms for images ciphered by stream cipher schemes all have approximately flat histogram less information as compared to one-dimensional ciphering algorithms and threshold generator-based image ciphering scheme. Furthermore, the stream cipher schemes were effectively applied to the colored images of 256-color levels of true-color images (24 bit). In this paper, we try to decrypt automatically using artificial neural network by decryption through multilayer perceptron and radial basis function; networks were tested using the interface by calculating the error rates of decrypted images. Springer Verlag (Germany) 2016 Article PeerReviewed Al Azawee, H. and Husien, S. and Yunus, M.A.M. (2016) Encryption function on artificial neural network. Neural Computing and Applications, 27 (8). pp. 2601-2604. ISSN 0941-0643, DOI https://doi.org/10.1007/s00521-015-2028-3 <https://doi.org/10.1007/s00521-015-2028-3>. https://doi.org/10.1007/s00521-015-2028-3 doi:10.1007/s00521-015-2028-3 |
| spellingShingle | QA75 Electronic computers. Computer science Al Azawee, H. Husien, S. Yunus, M.A.M. Encryption function on artificial neural network |
| title | Encryption function on artificial neural network |
| title_full | Encryption function on artificial neural network |
| title_fullStr | Encryption function on artificial neural network |
| title_full_unstemmed | Encryption function on artificial neural network |
| title_short | Encryption function on artificial neural network |
| title_sort | encryption function on artificial neural network |
| topic | QA75 Electronic computers. Computer science |
| work_keys_str_mv | AT alazaweeh encryptionfunctiononartificialneuralnetwork AT husiens encryptionfunctiononartificialneuralnetwork AT yunusmam encryptionfunctiononartificialneuralnetwork |