The human hand can copy all that the human hand creates", said Baron von Eichtal in 1843 when he was in charge of banknote issuing for the bank of Bavaria. Despite all the advancements in security printing and anti-counterfeiting, these words ring more true than ever. Indeed in the last thirty years, counterfeiters have greatly benefited from the globalisation of supply chains as well as from the digitization of production methods. Yet the development of digital technologies has also opened unprecedented possibilities for addressing the 3000 years old problem of counterfeiting. This presentation will review some of the counterfeit detection techniques developed in the last 20 years, including printed digital watermarks, copy detection patterns and secure QR Codes. These technologies not only open up the possibility for potentially anyone to verify authenticity with their smartphones, but they also enable the digitization of the trillions of physical documents, packaging and products that we produce every year. Real world examples from industrial applications as well as current research topics will be discussed.

Serialized QR Codes applied to product packaging have received considerable interest as a potential solution to the problem of industrial counterfeiting. Compared to traditional security solutions (e.g. taggants, holograms, security inks), they are indeed simpler to integrate in existing production workflow, easier to verify, and more cost-effective at scale. In addition, they allow to convey a product digital identity and history, and are used to connect brand owners with consumers. However, by itself a QR Code offers no protection at all against copy by cloning. Various schemes have been proposed to add a copy-sensitive layer to QR Codes, but most techniques in the state of the art have not been applied to real production environments, where QR Codes are printed at mass scale and products are scanned in a non-controlled environment, typically by consumers with their smartphones. This paper presents a system based on integrating copy detection patterns into QR Codes, which has been deployed for a number of years on the market.

In most watermarking systems, masking models, inherited from data compression algorithms, are used to preserve fidelity by controlling the perceived distortion resulting from adding the watermark to the original signal. So far, little attention has been paid to the consequences of using such models on a key design parameter: the robustness of the watermark to intentional attacks. The goal of this paper is to demonstrate that by considering fidelity alone, key information on the location and strength of the watermark may become available to an attacker; the latter can exploit such knowledge to build an effective mask attack. First, defining a theoretical framework in which analytical expressions for masking and watermarking are laid, a relation between the decrease of the detection statistic and the introduced perceptual distortion is found for the mask attack. The latter is compared to the Wiener filter attack. Then, considering masking models widely used in watermarking, experiments on both simulated and real data (audio and images) demonstrate how knowledge on the mask enables to greatly reduce the detection statistic, even for small perceptual distortion costs. The critical tradeoff between robustness and distortion is further discussed, and conclusions on the use of masking models in watermarking drawn.

Abstract Fast, effective, and adaptable techniques are needed to automatically organize and retrieve information on the ever‐increasing World Wide Web. In that respect, different strategies have been suggested to take hypertext links into account. For example, hyperlinks have been used to (1) enhance document representation, (2) improve document ranking by propagating document score, (3) provide an indicator of popularity, and (4) find hubs and authorities for a given topic. Although the TREC experiments have not demonstrated the usefulness of hyperlinks for retrieval, the hypertext structure is nevertheless an essential aspect of the Web, and as such, should not be ignored. The development of abstract models of the IR task was a key factor to the improvement of search engines. However, at this time conceptual tools for modeling the hypertext retrieval task are lacking, making it difficult to compare, improve, and reason on the existing techniques. This article proposes a general model for using hyperlinks based on Probabilistic Argumentation Systems, in which each of the above‐mentioned techniques can be stated. This model will allow to discover some inconsistencies in the mentioned techniques, and to take a higher level and systematic approach for using hyperlinks for retrieval.

Previous research has shown that hypertext links may be a useful source of evidence for document contents and relevance, but these evidence are rather difficult to represent and combine.This paper introduces a new and sound model for representing and handling hypertext links in IR.This model is based on ctProbabilistic Argumentation Systems )), a technique which combines logic and probability to handle uncertainty.Some experiments show the potential of this approach, which requires no ad-hoc parameters.