Intrinsic authentication of multimedia objects using biometric data manipulation

The Biometric-Gaussian-Stream (BGS) cryptosystem was extended by extensive research experimentation. Using this system, complexity is added to an image by passing it through a Gaussian noise function. This function is applied with specific parameters for the mean and variance, which also works as a parallel key. To implement a stream cipher (BGS) with help of biometric images, the Initial Condition (IC) for (Linear Feed Back Shift Register) LFSR from is extracted iriscode. A comparison between various stream ciphers is also made to measure the strength of the BGS cryptosystem. The previous experimentation work has been extended by formulating the algorithmic runtime complexity of the BGS Cryptosystem which proves to be O (n) algorithmically. New techniques to encrypt and assess multimedia objects have been introduced

Intrinsic Authentication of Multimedia Objects using Biometric Data Manipulation

The Biometric-Gaussian-Stream(BGS) cryptosystem was extended by extensive research experimentation. Using this system, complexity is added to an image by passing it through a Gaussian noise function. This function is applied with specific parameters for the mean and variance, which also works as a parallel key. To implement a stream cipher (BGS) with help of biometric images, the “Initial Condition (IC) for LFSR (Linear Feed Back Shift Register) from is extracted iriscode. A comparison between various stream ciphers is also made to measure the strength of the BGS cryptosystem. The previous experimentation work has been extended by formulating the algorithmic runtime complexity of the BGS Cryptosystem which proves to be O(n) algorithmically. New techniques to encrypt and assess multimedia objects have been introduce