short-paper

Estimation of Copy-sensitive Codes Using a Neural Approach

Authors:

Iuliia Tkachenko,

Alain Trémeau,

Thierry FournelAuthors Info & Claims

IH&MMSec'19: Proceedings of the ACM Workshop on Information Hiding and Multimedia Security

Pages 77 - 82

https://doi.org/10.1145/3335203.3335718

Published: 02 July 2019 Publication History

Abstract

Copy sensitive graphical codes are used as anti-counterfeiting solution in packaging and document protection. Their security is funded on a design hard-to-predict after print and scan. In practice there exist different designs. Here random codes printed at the printer resolution are considered. We suggest an estimation of such codes by using neural networks, an in-trend approach which has however not been studied yet in the present context. In this paper, we test a state-of-the-art architecture efficient in the binarization of handwritten characters. The results show that such an approach can be successfully used by an attacker to provide a valid counterfeited code so fool an authentication system.

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Cited By

Belousov YQuétant GPulfer BChaban RTutt JTaran OHolotyak TVoloshynovskiy S(2024)A Machine Learning-Based Digital Twin for Anti-Counterfeiting Applications With Copy Detection PatternsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.336179819(3395-3408)Online publication date: 2024
https://doi.org/10.1109/TIFS.2024.3361798
Tutt JTaran OChaban RPulfer BBelousov YHolotyak TVoloshynovskiy S(2024)Authentication of Copy Detection Patterns: A Pattern Reliability Based ApproachIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.335951019(3124-3134)Online publication date: 2024
https://doi.org/10.1109/TIFS.2024.3359510
Taran OTutt JHolotyak TChaban RBonev SVoloshynovskiy S(2023)Mobile authentication of copy detection patternsEURASIP Journal on Information Security10.1186/s13635-023-00140-52023:1Online publication date: 6-Jun-2023
https://doi.org/10.1186/s13635-023-00140-5
Show More Cited By

Index Terms

Estimation of Copy-sensitive Codes Using a Neural Approach
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks
2. Security and privacy
  1. Security services
    1. Authentication

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Information & Contributors

Information

Published In

cover image ACM Conferences

IH&MMSec'19: Proceedings of the ACM Workshop on Information Hiding and Multimedia Security

July 2019

249 pages

ISBN:9781450368216

DOI:10.1145/3335203

General Chairs:
Rémi Cogranne
Troyes University of Technology, France
,
Luisa Verdoliva
University Federico II of Naples, Italy
,
Program Chairs:
Siwei Lyu
University at Albany, New York, USA
,
Juan Pastoriza
Ecole polytechnique fédérale de Lausanne, Switzerland
,
Xinpeng Zhang
Shanghai University, China

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 July 2019

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IH&MMSec '19

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SIGMM

IH&MMSec '19: ACM Information Hiding and Multimedia Security Workshop

July 3 - 5, 2019

Paris, France

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Overall Acceptance Rate 128 of 318 submissions, 40%

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Citations

Cited By

Belousov YQuétant GPulfer BChaban RTutt JTaran OHolotyak TVoloshynovskiy S(2024)A Machine Learning-Based Digital Twin for Anti-Counterfeiting Applications With Copy Detection PatternsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.336179819(3395-3408)Online publication date: 2024
https://doi.org/10.1109/TIFS.2024.3361798
Tutt JTaran OChaban RPulfer BBelousov YHolotyak TVoloshynovskiy S(2024)Authentication of Copy Detection Patterns: A Pattern Reliability Based ApproachIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.335951019(3124-3134)Online publication date: 2024
https://doi.org/10.1109/TIFS.2024.3359510
Taran OTutt JHolotyak TChaban RBonev SVoloshynovskiy S(2023)Mobile authentication of copy detection patternsEURASIP Journal on Information Security10.1186/s13635-023-00140-52023:1Online publication date: 6-Jun-2023
https://doi.org/10.1186/s13635-023-00140-5
Zeghidi HCrispim-Junior CTkachenko I(2023)CDP-Sim: Similarity Metric Learning to Identify the Fake Copy Detection Patterns2023 IEEE International Workshop on Information Forensics and Security (WIFS)10.1109/WIFS58808.2023.10374744(1-6)Online publication date: 4-Dec-2023
https://doi.org/10.1109/WIFS58808.2023.10374744
Tutt JTaran OChaban RPulfer BBelousov YHolotyak TVoloshynovskiy S(2022)Mathematical model of printing-imaging channel for blind detection of fake copy detection patterns2022 IEEE International Workshop on Information Forensics and Security (WIFS)10.1109/WIFS55849.2022.9975447(1-6)Online publication date: 12-Dec-2022
https://doi.org/10.1109/WIFS55849.2022.9975447
Chaban RTaran OTutt JBelousov YPulfer BHolotyak TVoloshynovskiy S(2022)Printing variability of copy detection patterns2022 IEEE International Workshop on Information Forensics and Security (WIFS)10.1109/WIFS55849.2022.9975380(1-6)Online publication date: 12-Dec-2022
https://doi.org/10.1109/WIFS55849.2022.9975380
Xie NChen JChen YHu JZhang QChen CHuang L(2022)Detection of Information Hiding at Anti-Copying 2D BarcodesIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2021.305909232:1(437-450)Online publication date: Jan-2022
https://doi.org/10.1109/TCSVT.2021.3059092
Pulfer BChaban RBelousov YTutt JTaran OHolotyak TVoloshynovskiy S(2022)Authentication Of Copy Detection Patterns Under Machine Learning Attacks: A Supervised Approach2022 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP46576.2022.9897700(1296-1300)Online publication date: 16-Oct-2022
https://doi.org/10.1109/ICIP46576.2022.9897700
Tkachenko ITremeau AFournel T(2022)Protecting Documents Using Printed Anticopy ElementsMultimedia Security 210.1002/9781119987390.ch2(31-58)Online publication date: Jul-2022
https://doi.org/10.1002/9781119987390.ch2
Taran OTutt JHolotyak TChaban RBonev SVoloshynovskiy S(2021)Mobile authentication of copy detection patterns: how critical is to know fakes?2021 IEEE International Workshop on Information Forensics and Security (WIFS)10.1109/WIFS53200.2021.9648398(1-6)Online publication date: 7-Dec-2021
https://doi.org/10.1109/WIFS53200.2021.9648398
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