Distortion metrics for predicting authentication functionality of printed security deterrents

Gaubatz, Matthew; Simske, Steven J.; Gibson, Shawn

doi:10.1109/icip.2009.5414608

Cited by 8 publications

(7 citation statements)

References 8 publications

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“…The two final features are computed by averaging the following calculations over the R, G and B color channels: the average per-channel standard deviation, where the individual standard deviations are weighted by the fraction of non-white pixels in the associated color class, and the standard deviation of all the per-channel means. Note that these 36 + 2 + 2 = 40 features can be computed based on any image data, i.e., they represent generalized versions of previously described features [6,8] that were designed specifically for scanned color tiles. On the other hand, one might only expect the features to be useful in the cases where the markings were formed with a relatively small number of distinct colors.…”

Section: Color-class-based Featuresmentioning

confidence: 99%

“…Details about how color tile patterns are structured, how they are decoded, and what features are computed from them for classification purposes are described in [6,8]. Guilloche curve patterns are formed with combinations of solid color regions, but the spatial relationships between the regions are more sophisticated since the regions are composed of groups of polar curves.…”

Section: Structured Image Datamentioning

confidence: 99%

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Towards a feature set for robust printing-imaging cycle device identification using structured printed markings

Gaubatz

Simske

2010

2010 IEEE International Workshop on Information Forensics and Security

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Device identification is an emerging field where technologies used to create a digital image are inferred by strategic image analysis. Some of the more well understood topics in this area include techniques to identify cameras, scanners and printers. The goal of printing-imaging cycle device identification is to gather information about the printing and imaging devices used to create, then digitally reacquire, a physical document. It has been shown that accurate printer-scanner identification is possible using a specific type of marking composed of oriented, colored tiles. This paper discusses a set of features based on histogram analysis that can be applied to printingimaging device identification problems using a wider range of small structured markings (color tile deterrents and Guilloche curve patterns). The features are robust to a number of different effects, including changes in perspective and scan resolution. The approach results in superior identification performance in comparison to other state-of-the-art strategies, and more robustness to marking orientation. Performance as a function of scan resolution is also discussed in detail.

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Section: Color-class-based Featuresmentioning

confidence: 99%

Section: Structured Image Datamentioning

confidence: 99%

Towards a feature set for robust printing-imaging cycle device identification using structured printed markings

Gaubatz

Simske

2010

2010 IEEE International Workshop on Information Forensics and Security

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“…Support Vector Machines (SVM) appears to be widely used throughout the literature and promise a wide variety of applications such as banknote classification [76,77,78,79,80,81]. SVM is successfully implemented to recognize serial numbers on banknotes [82], and used for detection of stains to determine worn out banknotes [81].…”

Section: ) Authenticating Security Componentsmentioning

confidence: 99%

“…It is shown in [34,35,36,40,78,79,105,106], print anomalies can be detected and calculated to create a signature based on pixel distribution and satellite droplets. Similarly texture analysis of paper [41,47] investigates various qualities of the texture and roughness of surfaces relating to documents and banknotes, similarly [42] investigates the texture of the ink pattern.…”

Section: Trendsmentioning

confidence: 99%

Currency security and forensics: a survey

Chambers

Yan

Garhwal

et al. 2014

Multimed Tools Appl

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Abstract-By its definition, the word 'currency' refers to an agreed medium for exchange, a nation's currency is the formal medium enforced by the elected governing entity. Throughout history, issuers have faced one common threat: counterfeiting. Despite technological advancements, overcoming counterfeit production remains a distant future. Scientific determination of authenticity requires a deep understanding of the raw materials and manufacturing processes involved. This survey serves as a synthesis of the current literature to understand the technology and the mechanics involved in currency manufacture and security, whilst identifying gaps in the current literature. Ultimately, a robust currency is desired.

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“…Because of both the defaults of the physical process and the stochastic nature of the matter, this interaction can be considered as a physically unclonable function (PUF) [4] that cannot be reproduced by the forger and can consequently be used to perform authentication. In [5], the authors measure the degradation of the inks within printed color tiles and use discrepancy between the statistics of the authentic and print-and-scan tiles to perform authentication. Other marking techniques can also be used; in [6], the authors propose to characterize the random profiles of laser marks on materials such as metals (the technique is called LPUF for laser-written PUF) to use them as authentication features.…”

Section: Addressed Problem and Related Workmentioning

confidence: 99%

Document authentication using graphical codes: reliable performance analysis and channel optimization

Hoang

Sawaya

et al. 2014

EURASIP J. on Info. Security

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This paper proposes to investigate the impact of the channel model for authentication systems based on codes that are corrupted by a physically unclonable noise such as the one emitted by a printing process. The core of such a system for the receiver is to perform a statistical test in order to recognize and accept an original code corrupted by noise and reject any illegal copy or a counterfeit. This study highlights the fact that the probability of type I and type II errors can be better approximated, by several orders of magnitude, when using the Cramér-Chernoff theorem instead of a Gaussian approximation. The practical computation of these error probabilities is also possible using Monte Carlo simulations combined with the importance sampling method. By deriving the optimal test within a Neyman-Pearson setup, a first theoretical analysis shows that a thresholding of the received code induces a loss of performance. A second analysis proposes to find the best parameters of the channels involved in the model in order to maximize the authentication performance. This is possible not only when the opponent's channel is identical to the legitimate channel but also when the opponent's channel is different, leading this time to a min-max game between the two players. Finally, we evaluate the impact of an uncertainty for the receiver on the opponent channel, and we show that the authentication is still possible whenever the receiver can observe forged codes and uses them to estimate the parameters of the model.

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Distortion metrics for predicting authentication functionality of printed security deterrents

Cited by 8 publications

References 8 publications

Towards a feature set for robust printing-imaging cycle device identification using structured printed markings

Towards a feature set for robust printing-imaging cycle device identification using structured printed markings

Currency security and forensics: a survey

Document authentication using graphical codes: reliable performance analysis and channel optimization

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