TY - GEN
T1 - Machine Learning-Based Methods in Source Camera Identification
T2 - 2022 International Conference on Business Analytics for Technology and Security, ICBATS 2022
AU - Gouda, Omar
AU - Bouridane, Ahmed
AU - Talib, Manar Abu
AU - Nasir, Qassim
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Source identification is one of the most critical problems in the field of multimedia forensics. In the last decade, researchers have been studying and improving in this field. Photo Response Non-Uniformity is one of the unique noise patterns that is being used to match a media to its originating device. Utilizing the noise patterns with machine learning algorithms has been the focus of research in recent years. Therefore, a systematic review is needed to present the latest contributions in this field. This systematic review focuses on the published work from 2015 to 2021 in source identification using noise patterns in machine learning-based systems. The results of the review indicate that a benchmark should be proposed and used to fairly compare past and future methods. Moreover, a minimum number of devices used for evaluating a model should be set by the research community in order to accurately evaluate the accuracy of the model in real-life situations.
AB - Source identification is one of the most critical problems in the field of multimedia forensics. In the last decade, researchers have been studying and improving in this field. Photo Response Non-Uniformity is one of the unique noise patterns that is being used to match a media to its originating device. Utilizing the noise patterns with machine learning algorithms has been the focus of research in recent years. Therefore, a systematic review is needed to present the latest contributions in this field. This systematic review focuses on the published work from 2015 to 2021 in source identification using noise patterns in machine learning-based systems. The results of the review indicate that a benchmark should be proposed and used to fairly compare past and future methods. Moreover, a minimum number of devices used for evaluating a model should be set by the research community in order to accurately evaluate the accuracy of the model in real-life situations.
KW - Machine Learning (ML)
KW - Photo Response Non-Uniformity (PRNU)
KW - Source Camera Identification
KW - Source Smartphone Identification
KW - Systematic Literature Review (SLR)
UR - https://www.scopus.com/pages/publications/85129598740
U2 - 10.1109/ICBATS54253.2022.9759089
DO - 10.1109/ICBATS54253.2022.9759089
M3 - Conference contribution
AN - SCOPUS:85129598740
T3 - 2022 International Conference on Business Analytics for Technology and Security, ICBATS 2022
BT - 2022 International Conference on Business Analytics for Technology and Security, ICBATS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 16 February 2022 through 17 February 2022
ER -