Automated Border Control Systems Research Articles

Smart Automated Border Control System for Pakistan Airports Using ML-based Biometric Measures

With the global population on the rise, the substantial increase in cross-border travel poses heightened security risks, the potential for the spread of pandemics such as COVID-19, congestion, delays in the check-in and checkout process, and various other challenges. This paper introduces a novel smart Automated Border Control system referred to as ABC system tailored for Pakistan. Employing advanced biometric technologies, including contactless facial and palm recognition systems, the proposed system aims to mitigate the spread of the COVID-19 pandemic at border crossings. A travel document reader system, leveraging Optical Character Recognition (OCR) technology, retrieves passport-based information from the database. State-of-the-art machine learning-based facial recognition algorithms and recent contactless palm recognition methodologies authenticate and validate passengers entering Pakistan. Furthermore, the proposed system is designed for seamless integration with existing services such as the Integrated Border Management System (IBMS) for immigration, Exit Control List (ECL), NADRA (National Database and Registration Authority) database, online Visa database, Passport database, and Advance Passenger Information (API) or Passenger Name Record (PNR) systems. By expediting the authentication process, the system significantly reduces delays in immigration procedures.

Testing and evaluation of the Automated Border Control System

AbstractAim: The aim of the study is to present the circumstances and results of the operational test and evaluation of the Automated Border Control System to be implemented in 2021 on the Hungarian-Ukrainian (Schengen external) border. The focus is on the operational efficiency of the system.Methodology: Through document and content analysis, we examined the theoretical and legal background of the system, its regulatory environment, and in order to achieve the results, we carried out a qualification measurement based on tool- and method-specific criteria.Findings: Measurements and evaluations have shown that, in terms of the ratio between the human resources used in border checks and the time taken to carry out the checks, the checks carried out by the automated border control system have proved to be more efficient.Value: The testing and evaluation of the kiosks and automated (fixed) gates that make up the components of the Automated Border Control System at Schengen external land border crossing points has not been carried out before in Hungary, and therefore this study and the study based on it are unique i n the border policing area.

A multi-agent based enhancement for multimodal biometric system at border control

Border criminals and unauthorized immigrants are dramatically increasing within the last few years in globally due to the absence of proper authorization methods at the border locations. Usually, passenger controls done by trained immigration officers who compare the passport and the physical appearance at the border while some of the countries done by automated border control (ABC) systems. ABC is one of the applicable real-world applications of the biometric domain which commonly implements with fingerprint and face (multimodal) biometric authorization. However, selecting an appropriate classification method is a challenging task at the decision-making stage. This paper proposes a novel architecture for multimodal biometric authorization engaged with the multi-agent system (MAS) to come up with the optimal solution by using the co-feature of MAS, such as coordination, corporation, and negotiation features. The experiment was done with four available multimodal datasets, namely, the National Institute of Standard Technology (NIST) multimodal, SDUMLA-HMT multimodal, BANCA and PRIVATE databases have been reported to demonstrate the efficiency of the proposed method. The experimental result delivers an excellent performance comparing with previous ABC systems at the authentication phase and computationally fast.

Face morphing attack detection and attacker identification based on a watchlist

Face verification is widely used for Automated Border Control (ABC) in many countries. But such ABC systems are vulnerable to Morphing Attacks (MAs), where a morphed face image is submitted to apply for a passport. To counter face MAs, this paper proposes to detect morphed face images and identify morphing attackers by the use of a watchlist. It is carried out by comparing a suspect image with the biometric references contained in a watchlist, and its detection process is accomplished by analyzing the results of face comparison. Once a morphed image is detected, its morphing attacker is also identified. Meanwhile, a database with different morphing methods, image qualities, facial expressions, and face angles is collected. Experimental results and analysis show that it can achieve stable detection and attacker identification performance for 4 different face MAs, and it can well generalize to unseen morphing types and weights. Moreover, it has good robustness to variations of image qualities, facial expressions, and face angles.

Automated border control systems: A literature review

Automated Border Control (ABC) systems are intelligent systems that are used nowadays at various international airports. ABC systems are widely used in airports' arrival and departure areas to accommodate the increase in passenger flow and air traffic, with the aim of promoting travel while retaining the security of worldwide border crossing joints. The instability faced by this development, such as disruption at immigration and security departments or delays in expected arrival patterns, are dealt with by ABC systems. These systems use a variety of approaches at airports, including face recognition, fingerprint, iris recognition, and E-passport. For effective quality and durability, face recognition systems need elevated facial images. In this paper, various research has been critically reviewed and a summary of literature review has been performed based on the existing relevant literature. The range of papers included basic E-gates located at airports in different countries, some analyzing different propaganda connected to it.

Air Passengers’ Continued Use Intention of the Airport E-Gate System: A Perspective with Perceived Benefits

With the rapid development of air transportation in recent years, the number of national entry and exit passengers has hit record highs. Facing the increasingly busy airport, an automated border control system (E-gate) has been developed to provide faster and more convenient services. This study adopts the perspective of perceived benefits to explore the willingness of passengers to continuously use the E-Gate. In this study, a total of 539 valid questionnaires are collected at the Taoyuan International Airport in Taiwan. The SPSS 24 and AMOS 22 software are used for statistical analysis, and the hypotheses are verified by Structural Equation Modeling (SEM). The results show that perceived ease of use, perceived usefulness, and convenience have positive and significant effects on air passengers’ continued use intention of E-gate, with convenience having the greatest impact, followed by perceived ease of use and perceived usefulness. The findings of this research can not only assist government agencies and airport operators in the development of better user-accepted immigration clearance systems, but can also provide insight into how to promote the new technology to potential users.

Convolutional Neural Network Approach for Multispectral Facial Presentation Attack Detection in Automated Border Control Systems.

Automated border control systems are the first critical infrastructure point when crossing a border country. Crossing border lines for unauthorized passengers is a high security risk to any country. This paper presents a multispectral analysis of presentation attack detection for facial biometrics using the learned features from a convolutional neural network. Three sensors are considered to design and develop a new database that is composed of visible (VIS), near-infrared (NIR), and thermal images. Most studies are based on laboratory or ideal conditions-controlled environments. However, in a real scenario, a subject’s situation is completely modified due to diverse physiological conditions, such as stress, temperature changes, sweating, and increased blood pressure. For this reason, the added value of this study is that this database was acquired in situ. The attacks considered were printed, masked, and displayed images. In addition, five classifiers were used to detect the presentation attack. Note that thermal sensors provide better performance than other solutions. The results present better outputs when all sensors are used together, regardless of whether classifier or feature-level fusion is considered. Finally, classifiers such as KNN or SVM show high performance and low computational level.

Dynamic facial presentation attack detection for automated border control systems

Millions of passengers travel every day, border crossing being one of their most common activities. At these points it is extremely important that security is completely guaranteed. However, the maintaining adequate security levels is a very demanding issue. This has promoted the development of systems capable of providing support to border authorities by automatising some of their tasks. Thus, Automated Border Control (ABC) systems have become a key tool. These systems increase the flow of travellers as they can achieve fast evaluations of individuals through their machine-readable travel documents. However, this has motivated the appearance of attacks that try to avoid the identity detection of individuals by these systems. Presentation Attack Detection (PAD) algorithms have emerged to mitigate such a problem. This paper presents the On-the-Fly Presentation Attack Detection (FlyPAD) framework that implements a set of dynamic PAD techniques. It allows multiple types of attacks to be detected as the traveller approaches the ABC system, rather than being static in front of the cameras. Several experiments have been carried out, both in the laboratory and in real environments, obtaining promising results.

Border Control Morphing Attack Detection with a Convolutional Neural Network De-morphing Approach

Currently, the use of biometric identification, automated or semiautomated, is a reality. For this reason, the number of attacks has increased in such systems. One of the most common biometric attacks is the presentation attack (PA) because it is relatively easy to perform. Automated border control (ABC) is a clear target for phishers. Concerning biometric attacks, morphing is one of the most threatening attacks because authentication systems are usually unable to correctly detect them. In this attack, a fake face is generated with the morphing and blending of two different subjects (genuine and phisher), and the image result is stored in the passport. These attacks can generate risky situations in cases of border crossings where an ABC system should perform identification tasks. This research work proposes a de-morphing architecture that is founded on a convolutional neural network (CNN) architecture. This technique is based on the use of two images: the potentially morphed image stored in the passport, and the snapshot of the person located in the ABC system. The goal of the de-morphing process is to unravel the chip image. If the chip image is a morphed one, the revealing process between the in vivo image and the morphed chip image will return a different facial identity to the person located in the ABC system, and the impostor will be uncovered in situ . If the chip image is a non-morphing image, the resulting image will be similar to a genuine passenger. Therefore, the information obtained is considered at the border crossing. The equal error rate (EER) achieved is very low compared to the literature values published to date. The accomplished outcomes endorse a robust method that provides high accuracy rates without taking into account the quality of images used. This key point is crucial to plausible deployment plans in areas such as ABC.

Face Demorphing

The morphing attack proved to be a serious threat for modern automated border control systems where face recognition is used to link the identity of a passenger to his/her e-document. In this paper, we show that by exploiting the live face image acquired at the gate, the morphed face image stored in the document can be reverted (or demorphed) enough to reveal the identity of the legitimate document owner, thus allowing the system to issue a warning. A number of practical experiments on two data sets proves the efficacy of our approach.

The requirement of accessibility: European automated border control systems for persons with disabilities

This exploratory study investigates whether automated border control systems should be provided for persons with disabilities at European airports. While the special assistance provided to disabled passengers has improved in the last decade, some may want to travel independently using automated gates. This is currently not possible, nor is there an explicit plan to include the accessibility requirement in future technology development. We reflect this questionable situation against the notion of the good society and consider airports as normatively laden socio-physical zones contributing to experiences of exclusion. Our research stresses the need to consider human abilities as a spectrum, which should be addressed with the use of universal design principles to benefit as many travelers as possible. Interviews and a survey of disabled passengers help us explore the views of stakeholders; to find out whether persons with disabilities wish to use automated systems instead of assistance services, and whether stakeholders consider accessible systems technologically possible, cost-effective, and recommendable.

Smart and secure borders through automated border control systems in the EU? The views of political stakeholders in the Member States

ABSTRACTThe European Commission launched the “Smart Borders” policy process in 2011 to enhance border security in the European Union (EU) using technologisation and harmonisation. This includes the use of automated border control (ABC) systems. The Member States crucially shape the process, weighing security technologies and costs, privacy and rights, and further institutional choices. We examine the views of political stakeholders in four Member States by conducting a systematic empirical and comparative study unprecedented in the existing, political-theory-inspired research. In our Q methodological experiments, political stakeholders in Finland, Romania, Spain and the UK rank-ordered a sample of statements on Smart Borders, ABC and harmonisation. The factor analysis of the results yielded three main views: the first criticising ABC as a security technology, the second welcoming the security gains of automation and the third opposing harmonised border control. While impeding harmonisation, the results offer a consensus facilitating common policy.

Automated border control e-gates and facial recognition systems

A fast automated biometric solution has been proposed to satisfy the future border control needs of airports resulting from the rapid growth in the number of passengers worldwide. Automated border control (ABC) systems handle the problems caused by this growth, such as congestion at electronic gates (e-gates) or delays in the planned arrival schedules. Different modalities, such as face, fingerprint, or iris recognition, will be used in most of the ABC systems located at airports in the European/Schengen areas. Because facial recognition is the modality that travelers consider most acceptable, it was decided to include this modality in all second generation passports. Face recognition systems, installed in small kiosks inside the e-gates, require high quality facial images to allow high performance and efficiency. Accurate face recognition algorithms, which should be invariant to non-idealities, such as changes in pose and expression, occlusions, and changes in lighting, are also required for these systems. In this paper, a review of the most important face recognition algorithms described in the literature that are invariant to these non-idealities and that can be used in ABC e-gates is presented. A comparative analysis of the most common ABC e-gates located at the different airports is provided. In addition, the results of an experimental evaluation of a face recognition system when halogen, white LEDs, near infra-red, or fluorescence illumination was used, which was conducted in order to determine which type of illumination is optimal for use in ABC e-gates, are presented. To conclude, improvements that could be implemented in the near future in ABC face recognition systems are described.

Policy Requirements for Automated Border Control Systems: A Q Methodological Study of Finland in the Context of a Large European Research Project

With growing passenger volumes and pressures for secure identity control at the European Union’s borders, interest is growing in automating and harmonising border control processes. A large research project entitled FastPass and funded by the European Commission is developing solutions for this purpose. Ultimately, however, the funding decisions for the acquisition of automated border control devices and software are taken by national parliaments, making politicians key stakeholders in the process. We examine their subjective views on the socio-ethical, legal, political, and privacy requirements for these systems with the help of Q methodology. In this way we account for the concerns, risks, and opportunities they identify in these systems. This initial case study reports the policy preferences and requirements for automated border control as found in the views of political stakeholders in Finland. The findings indicate some apprehensions, for example, on privacy, but also hope of finding common ground. We discuss the implications of the findings for future, politically sustainable solutions in automated border control in the European Union, and the needs for further Q methodological analyses in this type of research context.

Policy Requirements for Automated Border Control Systems: A Q Methodological Study of Finland in the Context of a Large European Research Project

With growing passenger volumes and pressures for secure identity control at the European Union’s borders, interest is growing in automating and harmonising border control processes. A large research project entitled FastPass and funded by the European Commission is developing solutions for this purpose. Ultimately, however, the funding decisions for the acquisition of automated border control devices and software are taken by national parliaments, making politicians key stakeholders in the process. We examine their subjective views on the socio-ethical, legal, political, and privacy requirements for these systems with the help of Q methodology. In this way we account for the concerns, risks, and opportunities they identify in these systems. This initial case study reports the policy preferences and requirements for automated border control as found in the views of political stakeholders in Finland. The findings indicate some apprehensions, for example, on privacy, but also hope of finding common ground. We discuss the implications of the findings for future, politically sustainable solutions in automated border control in the European Union, and the needs for further Q methodological analyses in this type of research context.

Vision-Box puts up biometric periscope

Vision-Box, automated border control systems and electronic identity management solutions provider, has revealed its biometric periscope for simultaneous capture of face and iris, at a distance.