Integration of multimodal biometrics is widely explored for the purpose of security enhancement. Hence, in this research we deemed further to evaluate the integration of car plate and face recognition as security enhancement in parking lot. Firstly, the acquired face and car plate that acted as database is encrypted based on Hill Cipher matrix manipulation using random numbers and Fast Fourier Transform (FFT) as encryption algorithm. Next, Unconstrained Minimum Average Correlation Energy (UMACE) was applied for car plate recognition process during parking entrance in identifying the intruder via Peak to Side lobe Ratio (PSR) value. During exit, UMACE is once again utilized for both plate and face recognition for verification of registered driver based on decision fusion of PSR value. Results attained specifically Total Success Rate (TSR) of 96% during parking entrance along with over 99% during exit at PSR value of 10, confirmed that the proposed method is apt as security in parking space.