It is important to combat fraud on travel documents (e.g., passports), identity documents (e.g., ID-card) and breeder documents (e.g., birth certificates) to facilitate the travel of bona-fide travelers and to prevent criminal cross-border activities, such as terrorism, illegal migration, smuggling, and human trafficking. However, it is challenging and time consuming to verify all document security features manually. New technologies can assist in the automated fraud detection in these documents, which may result in faster and more consistent checks. This paper presents and evaluates four new technologies in automated document analysis. The first recognizes printing techniques. The second assists in the recognition of fraud in details. The third extracts information from the document, which can be used to detect anomalies at a tactical level. The fourth category concerns the analysis of travel patterns, using information from the visa pages in passports. The performance is assessed for each element with quantitative performance metrics.
Authentication of travel documents (e.g., passports) and breeder documents (e.g., birth certificates) is important to facilitate legal movement of passengers and to prevent cross-border crime, such as terrorism, smuggling, illegal migration and human trafficking. However, it is time consuming and difficult to verify all security features, the border guards differ in experience and expertise, and it is hard to stay alert every minute of a working day. New (artificial-intelligence based) technologies can assist in the automated fraud detection in travel and breeder documents, which may lead to faster and more consistent checks. This paper presents five categories of new technologies in automated document authentication to overcome the limitations of current document analysis systems in automated and non-automated border control scenarios. The first category consists of techniques related to the verification of visual security features on the holder page of travel documents. This category includes the verification of KINEGRAMs and other Optically Variable features under different light sources and lighting angles, and the analysis of printing techniques. The second category consists of techniques related to the analysis of breeder documents. This analysis can be at detail level (e.g., investigation of stamps) and at tactical level (e.g., verification of a check digit in a document number). The third category concerns the analysis of travel patterns, using information from the visa pages in passports. The stamps on these pages can be used to extract a travel pattern to support risk assessments and to detect anomalies. The fourth category is an analysis of the border-guard inspection history based upon a distributed ledger and blockchain technology that enables secure storage and prevents undesired manipulations. The last category analyzes the electronic chip of a passport. The software analyses document signer and country signer certificates on the chip to detect vulnerable cryptographic keys and tactical anomalies.
The current capabilities and capacities of border guards and immigration services can be enhanced using technologies that automate the analysis of travel, identity and breeder documents in order to detect fraud. These technologies can be relevant for countering emerging threats in document and identity verification (e.g., forged documents, impostor fraud, morphed faces) at both manual and highly automated border control points (both in the first and in the second line) and in the issuance process of genuine documents. The travel documents (e.g., passports) and breeder documents (e.g., birth certificates) contain personal information, such as name, date of birth and national number. The personal information must be well protected and a data breach must be avoided at all times. One of the ways to protect the personal data is to minimize the sharing of personal data. Anonymization removes the personal information (e.g., by replacing the personal information by a black bar) and can therefore be used to minimize the sharing of personal data. This paper describes the tool that assists border guards and immigration services for the anonymization of travel and breeder documents. The tool consists of a graphical user interface, document detection, keyword recognition, face detection, number detection, barcode detection and masking of personal data. The results show that only 10 annotated images are needed to reach a keyword detection accuracy of 96% and anonymization sensitivity of 93% of the related personal data.
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