Previous research has demonstrated that due to individual hardware imperfections in, e.g., the lenses of cameras, it is possible to attribute the pictures of a specific camera among a group of cameras. The goal of this thesis is to review the existing state-of-the-art and build a comprehensive framework of applied methods and features to perform either camera verification (binary output) or source camera attribution.

Although Python is the preferred programming language, the utilized programming language can vary based on the student's knowledge and preferences. 

References: 

1. "Digital Camera Identification from Sensor Pattern Noise", 2006
2. Choi et al., Feature Selection in Source Camera Identification", 2006
3. Filler et al., "Using Sensor Pattern Noise for Camera Model Identification", 2008
4. Alhussainy, "Forensic Source Camera Identification by Using Features in Machine Learning Approach", 2016
5. Rahim and Mohd Foozy, "Source Camera Identification for Online Social Network Images Using Texture Feature". 2020