Authentication of Copy Detection Patterns under Machine Learning Attacks: A Supervised Approach

doi:doi:10.57702/k5ra7rh6

Authentication of Copy Detection Patterns under Machine Learning Attacks: A Supervised Approach

Copy detection patterns (CDP) are an attractive technology that allows manufacturers to defend their products against counterfeiting. The main assumption behind the protection mechanism of CDP is that these codes printed with the smallest symbol size (1x1) on an industrial printer cannot be copied or cloned with sufficient accuracy due to data processing inequality.

BibTex:

@dataset{B_Pulfer_and_R_Chaban_and_Y_Belousov_and_J_Tutt_and_O_Taran_and_T_Holotyak_and_S_Voloshynovskiy_2024,
    abstract = {Copy detection patterns (CDP) are an attractive technology that allows manufacturers to defend their products against counterfeiting. The main assumption behind the protection mechanism of CDP is that these codes printed with the smallest symbol size (1x1) on an industrial printer cannot be copied or cloned with sufficient accuracy due to data processing inequality.},
    author = {B. Pulfer and R. Chaban and Y. Belousov and J. Tutt and O. Taran and T. Holotyak and S. Voloshynovskiy},
    doi = {10.57702/k5ra7rh6},
    institution = {No Organization},
    keyword = {'authentication', 'copy detection patterns', 'counterfeiting', 'deep learning', 'machine learning'},
    month = {dec},
    publisher = {TIB},
    title = {Authentication of Copy Detection Patterns under Machine Learning Attacks: A Supervised Approach},
    url = {https://service.tib.eu/ldmservice/dataset/authentication-of-copy-detection-patterns-under-machine-learning-attacks--a-supervised-approach},
    year = {2024}
}