000			a
999			_c13919 _d13919
003			OSt
005			20210107121131.0
008			210107b xxu||||| |||| 00| 0 eng d
040			_aAIKTC-KRRC _cAIKTC-KRRC
100			_912912 _aDevi Priya, K.
245			_aOffline Handwritten Signatures Based Multifactor Authentication in Cloud Computing using Deep CNN Model
250			_aVol.6(22), Jul-Dec
260			_aTamil Nadu _bi-manager's _c2019
300			_a13-25p.
520			_aCloud Security is an important factor that influences the adoption of cloud applications into bank domains. Many researchers proposed secure authentication mechanisms based on the traditional factors, biometric factors, captcha and certificates etc. This paper proposes a biometric handwritten signature recognition using Deep Convolution Neural Networks (DCNN). The proposed model uses signature as a biometric factor to verify the authenticity of the users along with traditional credentials. The extraction of the features are performed using DeepCNN model in the registration and verification process. The practical setup is done through NIVIDIA DGX environment using Python keras and tensor flow as backend. An experimental result shows 99% of accuracy and validation accuracy.
650		0	_94622 _aComputer Engineering
700			_912913 _aSumaltha, L.
773	0		_dNagercoil i-manager Publication _x 2349-6835 _ti-manager's journal on cloud computing (JCC)
856			_uhttps://imanagerpublications.com/article/16640/23 _yClick here
942			_2ddc _cAR