Abstract: For image based analysis in network implications, an important verified visual representation are applied which are termed as, ‘Convolution Neural Networks’. The existing Convolution Neural Networks process involves , ‘Time Series Classification’ were an image depicted as the data set are predicted to extract a pattern. Based on this pattern, exact specification to predict a concrete solution are allowed in the existing schemes. To enhance the existing system and to propose novelty in adapting the information security process. The existing system is adapted to undergo the process of appending secrecy bits in the original image are executed in this work. Further the secret pattern orientated image are transmitted to all other participating nodes, which ensures a secured transmission in the networks. After the quantization analysis of the existing models the secrecy image representation has produced considerably significant percentage of 5% increased protection measures with respect to its dataset image representation. Hence the proposed system evaluates the time series classification that are commonly used in Convolution Neural Networks and adopts security enhancement which proves that data are transmitted in a secured manner by utilizing the cryptography methods.
Keywords: Neural Network,, Cryptography , Information security.
Title: SECURITY ANALYSIS IN CONVOLUTIONAL NEURAL NETWORK USING TIME SERIES CLASSIFICATION AND CRYPTO SCHEMES
Author: S.KAVITHA, A.SENTHILKUMAR
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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