Title :
Neural network based decryption for random encryption algorithms
Author :
Munukur, Rathi Kannan ; Gnanam, Vignesh
Author_Institution :
Dept. of Electron. & Commun. Eng., PSG Coll. of Technol., Coimbatore, India
Abstract :
Typically encryption follows a specific rule with or without a key so that the cipher text can be decoded using the corresponding suitable decryption algorithm. This paper aims at removing the need for the encoding to follow a general rule by using a neural network for decoding the cipher text. Hence introducing the randomness in coding making it so much more difficult to decode. We have also introduced the concept of including lies in the information transmitted to misguide any eavesdropper who manages to decipher the cipher text. The presented results are obtained through the use of MATLAB 7.0.1.
Keywords :
backpropagation; cryptography; neural nets; MATLAB 7.0.1; cipher text decoding; decryption algorithm; neural network; random encryption algorithms; Artificial neural networks; Backpropagation; Cryptography; Decoding; Educational institutions; Encoding; Information security; MATLAB; Neural networks; Neurons; artificial neural networks; backpropagation neural nets; cryptography; decryption; encryption;
Conference_Titel :
Anti-counterfeiting, Security, and Identification in Communication, 2009. ASID 2009. 3rd International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-3883-9
Electronic_ISBN :
978-1-4244-3884-6
DOI :
10.1109/ICASID.2009.5277002