This study presents a novel method of authentication in digital environment in which each element of authentication is linked to one another. Having multiple factors to authenticate and deriving co-relations among these increases the safety and security of the device. Types of behavioral and acoustic patterns which are to be considered are GPS, accelerometer, microphone \& speaker fingerprint, lip \& tongue movement sensing and pinna shape sensing. Pattern data from different sensors is compared and cross checked. Having multiple factors to authenticate and deriving co-relations among these increases the security of device. The main advantage of multi factor behavioral authentication is that the verification is done dynamically and continuously to provide real time security. All authentication activities are carried out in the background without the user being interrupted. Furthermore, because these authentication approaches do not involve the user, the user experience is enhanced along with the security of the device.