Abstract- Finger vein recognition is an essential biometric identification technique that has become popular for securityenhancement in recent years. This paper presents various features sets examined in finger vein-based identification andverification systems. The system comprises of image acquisition, preprocessing, feature extraction, and decision-making.The different types of image acquisition techniques are light transmission, light reflection, bottom lighting, and sidelighting. The preprocessing techniques are further classified into quality evaluation, area of interest (ROI) selection,normalization, and enhancement. It modifies the acquired images for better analysis. The feature extraction includes veinpattern analysis, local pattern recognition, dimensionality reduction, and texture-shape descriptors to improveidentification. The acquired image is matched with the template stored in the database in the final stage. This paper alsopresents various challenges in finger vein recognition systems, but it primarily focuses on the challenges in presentationattack detection (PAD), that reduces the efficiency of the biometric systems. The limitations of PAD using federal learningare also discussed.