Mr.S.Vamshi Krushna, Voluru Saranya, Kotha Sneha, N Ajay Kumar Reddy, Bukya Rajkumar 02 10 Failure of facial recognition and authentication system may lead to several unlawful activities The current facial recognition systems are vulnerable to different biometric attacks This research focuses on morphing attack detection This research proposes a robust detection mechanism that can deal with variation in age illumination eye and head gears A deep learningbased feature extractor along with a classifier is adopted Additionally image enhancement and feature combination are proposed to augment the detection results A versatile dataset is also developed that contains Morph2 and Morph3 images created by sophisticated tools with manual intervention Morph3 images can give more realistic appearance and hence difficult to detect Moreover Morph3 images are not considered in the literature before Professional morphing software depicts more realistic morph attack scenario as compared to the morphs generated in the previous work from free programs and code scripts Eight face databases are used for creation of morphs to encompass the variation These databases are Celebrity2000 Extended Yale FEI FGNET GTDB MULTIPIE FERET and FRLL Results are investigated using multiple experimental setups and it is concluded that the proposed methodology gives promising results Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026