Publications

@article{bennabhaktula_source_2022,

title = {Source camera device identification from videos},

author = {Guru Swaroop Bennabhaktula and Derrick Timmerman and Enrique Alegre and George Azzopardi},

url = {https://link.springer.com/article/10.1007/s42979-022-01202-0},

year  = {2022},

date = {2022-01-01},

journal = {SN Computer Science},

volume = {3},

number = {4},

pages = {316},

abstract = {This paper addresses the problem of source camera identification in digital videos using deep learning. The authors evaluate different models for camera identification, showing that traditional scene-suppression techniques don't improve performance. They achieved state-of-the-art accuracy on the VISION and QUFVD datasets, outperforming previous methods. The proposed approach does not require flat frames, unlike traditional PRNU-based methods, and is more efficient, making it suitable for use by Law Enforcement Agencies (LEAs).},

note = {Publisher: Springer Nature Singapore Singapore},

keywords = {Camera Recognition, deep learning, Digital Image Forensics, Manchine Learning, Source Camera Identification},

pubstate = {published},

tppubtype = {article}

}

@article{bennabhaktula_camera_2022,

title = {Camera model identification based on forensic traces extracted from homogeneous patches},

author = {Guru Swaroop Bennabhaktula and Enrique Alegre and Dimka Karastoyanova and George Azzopardi},

url = {https://www.sciencedirect.com/science/article/pii/S0957417422010430},

year  = {2022},

date = {2022-01-01},

journal = {Expert Systems with Applications},

volume = {206},

pages = {117769},

abstract = {This work addresses the challenge of identifying the source camera model in digital image forensics, crucial for investigations by Law Enforcement Agencies. The proposed solution extracts small homogeneous regions from the integral image and uses a hierarchical classification approach with convolutional neural networks. This method outperforms traditional classifiers and achieves a 99.01% accuracy on the Dresden dataset’s ‘natural’ subset, marking the best result reported to date.},

note = {Publisher: Pergamon},

keywords = {Camera Model Identification, Digital Image Forensics, Sensor Pattern Noise},

pubstate = {published},

tppubtype = {article}

}