A Risk-Based Optimization Framework for Security Systems Upgrades at Airports

Airports are fast-growing dynamic infrastructure assets. For example, the Canadian airport industry is growing by 5% annually and generates about $8 billion yearly. Since the 9/11 tragedy, airport security has been of paramount importance both in Canada and worldwide. Consequently, in 2002, in the wake of the attacks, the International Civil Aviation Organization (ICAO) put into force revised aviation security standards and recommended practices, and began a Universal Security Audit Program (USAP), in order to insure the worldwide safeguarding of civil aviation in general, and of airports in particular, against unlawful interference. To improve aviation security at both the national level and for individual airport, airport authorities in North America have initiated extensive programs to help quantify, detect, deter, and mitigate security risk. At the research level, a number of studies have examined scenarios involving threats to airports, the factors that contribute to airport vulnerability, and decision support systems for security management. However, more work is still required in the area of developing decision support tools that can assist airport officials in meeting the challenges associated with decision about upgrades; determining the status of their security systems and efficiently allocating financial resources to improve them to the level required. To help airport authorities make cost-effective decisions about airport security upgrades, this research has developed a risk-based optimization framework. The framework assists airport officials in quantitatively assessing the status of threats to their airports, the vulnerability to their security systems, and the consequences of security breaches. A key element of this framework is a new quantitative security metric ; the aim of which is to assist airport authorities self-assess the condition of their security systems, and to produce security risk indices that decision makers can use as prioritizing criteria and constraints when meeting decisions about security upgrades. These indices have been utilized to formulate an automated decision support system for upgrading security systems in airports. Because they represent one of the most important security systems in an airport, the research focuses on passenger and cabin baggage screening systems. Based on an analysis of the related threats, vulnerabilities and consequences throughout the flow of passengers, cabin baggage, and checked-in luggage, the proposed framework incorporates an optimization model for determining the most cost-effective countermeasures that can minimize security risks. For this purpose, the framework first calculates the level of possible improvement in security using a new risk metric. Among the important features of the framework is the fact that it allows airport officials to perform multiple “what-if” scenarios, to consider the limitations of security upgrade budgets, and to incorporate airport-specific requirements. Based on the received positive feedback from two actual airports, the framework can be extended to include other facets of security in airports, and to form a comprehensive asset management system for upgrading security at both single and multiple airports. From a broader perspective, this research contributes to the improvement of security in a major transportation sector that has an enormous impact on economic growth and on the welfare of regional, national and international societies

Volatile Liquid Detection by Terahertz Technologies

The prospect of being able to move through security without the inconvenience of separating liquids from bags is an exciting one for passengers, and there are important operational benefits for airports as well. Here, two terahertz (THz) systems, 100 GHz sub-THz line scanner and attenuation total reflection-based THz time domain spectroscopy (TDS), have been used to demonstrate the capability of identifying different liquid samples. Liquid samples’ THz complex permittivities are measured and their differences have contributed to the variation of 100 GHz 2D images of volatile liquids with different volumes inside of cannister bottles. The acquired attenuation images at 100 GHz can easily be used to distinguish highly absorbed liquids (Water, Ethanol, Fuel Treatment Chemicals) and low loss liquids (Petrol, Diesel, Kerosene and Universal Bottle Cleaner). The results give a promising feasibility for mm-wave imager and THz spectroscopy to efficiently identify different volatile liquids

Inter-Dom Integrated Terminals - The Impact on Airlines Efficiency and Safety

This report performed research to assess the possibility of implementing hybrid passenger terminals. The benefits would be the integrating domestic and international passengers in the same restricted area. The initial hypothesis of this study was to focus on optimization that could bring advantages in terms of efficiency, customer service, and operational safety. The goal of this project was not to bring in-depth data on the topic, but to expose readers to the main players in the industry and understand the variables that impact the topic. Thus, although there are different perspectives on the integration of terminals, it was possible to identify some possible paths for future research. In addition, allow the industry itself to start discussions on the subject. The research team identified the need for a broad discussion involving all stakeholders to create a synergy of ideas and allow this discussion to evolve into a single front. Other than that, the study recommends a more accurate study related to the cost- benefit of this proposal. This would allow for the adaptation of a series of structural adaptations at airports. Such renovations could be compensated by increasing the use of Internal terminals, improving connection time by airlines, and improve customer experience regarding delays, procedures, service on the terminal. Regarding the topic of Operational Safety, the research team made recommendations for Brazilian authorities to invest in technologies that could facilitate not only what this research, but also bring more safety to passengers and bodies involved. This would be accomplished through the sharing of passengers information online between airlines and government. In addition, it recommended an investment so that the inspection of checked baggage was applied to all flights. This is because it is an important barrier to acts of unlawful interference, but also because it allows for more synergy with international protocols. To reach these conclusions, in addition to research with major international bodies such as IATA and ICAO, the group also understood ANAC\u27s perspective to establish current rules. Research also included the US model to support possible improvements in our system, understanding that the country operates with more advanced features than those we currently have in the country. In addition, to researching the available literature, professionals from some of these bodies, airlines, airports, and regulatory agencies were interviewed, which allowed a broad perspective of all players on how to proceed with the topic. Esse relatório propõe uma pesquisa inicial para avaliar a possibilidade de implementação de terminais híbridos, integrando passageiros domésticos e internacionais na mesma área restrita, com a hipótese inicial de que essa otimização poderia trazer benefícios em eficiência, experiência do cliente e segurança operacional. O objetivo desse projeto não é trazer dados aprofundados em relação ao tema, mas explora-los com os principais players da indústria e entender as variáveis que impactam o tema. Com isso, embora existam diferentes perspectivas relativas à integração de terminais, foi possível, identificar alguns possíveis caminhos para pesquisas futuras e mesmo para que a própria indústria inicie discussões relativas ao tema. O grupo identificou a necessidade de uma ampla discussão envolvendo todos os players para criar sinergia de idéias e permitir uma evolução nessa discussão em uma frente única. Fora isso, recomenda um estudo mais apurado relacionado ao custo-benefício dessa proposta, uma vez que a adequação envolve uma série de adaptações estruturais nos aeroportos, mas que podem ser compensadas ao aumentar a utilização de terminais e aumentar a utilização por empresas aéreas. Além de ajudar a melhorar a experiência do Internal cliente com as possíveis reduções nos atrasos, procedimentos padrões e serviços dentro dos terminais. No que tange o tema da Segurança Operacional, o grupo traz recomendações para que as autoridades Brasileiras invistam em tecnologias que possam facilitar não só o que se propõe essa pesquisa, mas também trazer mais segurança a passageiros e órgãos envolvidos, por meio do compartilhamento de informação de passageiros online entre empresas aéreas e governo. Além disso, recomenda um investimento para que a inspeção de bagagens despachadas seja aplicada para todos os voos, não só por ser uma importante barreira à atos de interferência ilícita, mas também por possibilitar mais sinergia com os protocolos internacionais. Para chegar nessas conclusões, além de pesquisas com os principais ógãos internacionais como IATA e ICAO, o grupo também entendeu a perspectiva da ANAC para estabelecer as regras atuais e usou o modelo norte-americano para suportar possíveis melhorias em nossos sistema, entendendo que o país opera com recursos mais avançados do que os que temos atualmente no país. Além das pesquisas na literatura disponível, foram entrevistados profissionais, de alguns desses Órgãos, Empresas Aéreas, Aeroportos e Agências Reguladoras o que nos permitiu uma perspectiva ampla de todos os players sobre como seguir com o tema

X-Ray Image Processing and Visualization for Remote Assistance of Airport Luggage Screeners

X-ray technology is widely used for airport luggage inspection nowadays. However, the ever-increasing sophistication of threat-concealment measures and types of threats, together with the natural complexity, inherent to the content of each individual luggage make x-ray raw images obtained directly from inspection systems unsuitable to clearly show various luggage and threat items, particularly low-density objects, which poses a great challenge for airport screeners. This thesis presents efforts spent in improving the rate of threat detection using image processing and visualization technologies. The principles of x-ray imaging for airport luggage inspection and the characteristics of single-energy and dual-energy x-ray data are first introduced. The image processing and visualization algorithms, selected and proposed for improving single energy and dual energy x-ray images, are then presented in four categories: (1) gray-level enhancement, (2) image segmentation, (3) pseudo coloring, and (4) image fusion. The major contributions of this research include identification of optimum combinations of common segmentation and enhancement methods, HSI based color-coding approaches and dual-energy image fusion algorithms —spatial information-based and wavelet-based image fusions. Experimental results generated with these image processing and visualization algorithms are shown and compared. Objective image quality measures are also explored in an effort to reduce the overhead of human subjective assessments and to provide more reliable evaluation results. Two application software are developed − an x-ray image processing application (XIP) and a wireless tablet PC-based remote supervision system (RSS). In XIP, we implemented in a user-friendly GUI the preceding image processing and visualization algorithms. In RSS, we ported available image processing and visualization methods to a wireless mobile supervisory station for screener assistance and supervision. Quantitative and on-site qualitative evaluations for various processed and fused x-ray luggage images demonstrate that using the proposed algorithms of image processing and visualization constitutes an effective and feasible means for improving airport luggage inspection

Application of signal detection theory to the recognition of objects in colour-encoded x-ray images

Aviation security personnel encounter problems when interpreting x-ray images of hand luggage. This research seeks to determine whether the performance of the human operator can be improved, in terms of both reliability and accuracy, through the employment of a novel multiple-view x-ray imaging technique. Thus, a series of experiments were undertaken with the aim of providing evidence for the feasibility of using KDEX displays to aid in the recognition of threatening objects in airport carry-on luggage; and furthermore demonstrate the real-world value of this technique. This thesis describes experiments comparing how introducing depth information affects the performance of aviation security personnel attempting to detect various weapons in x-ray images of hand luggage. Specifically, multiple 2-dimensional (2D) x-ray luggage scans were acquired and processed to create the perception of 3-dimensionality (3D) in kinetic displays. These results were compared with weapon detection in standard static 2D scans of the same luggage. Threatening objects hidden in this luggage were more readily detected in kinetic 3-dimensional images than in the standard images. Initial results were obtained using greyscale images and limited to various types of knives. Subsequent experiments evolved to primarily use pseudo-colour x-ray images

Microwave imaging for security applications

Microwave imaging technologies have been widely researched in the biomedical field where they rely on the imaging of dielectric properties of tissues. Healthy and malignant tissue have different dielectric properties in the microwave frequency region, therefore, the dielectric properties of a human body’s tissues are generally different from other contraband materials. Consequently, dielectric data analysis techniques using microwave signals can be used to distinguish between different types of materials that could be hidden in the human body, such as explosives or drugs. Other concerns raised about these particular imaging systems were how to build them cost effectively, with less radiation emissions, and to overcome the disadvantages of X-ray imaging systems. The key challenge in security applications using microwave imaging is the image reconstruction methods adopted in order to gain a clear image of illuminated objects inside the human body or underneath clothing. This thesis will discuss in detail how microwave tomography scanning could overcome the challenge of imaging objects concealed in the human body, and prove the concept of imaging inside a human body using image reconstruction algorithms such as Radon transformation image reconstruction. Also, this thesis presents subspace based TR-MUSIC algorithms for point targets and extended targets. The algorithm is based on the collection of the dominant response matrix reflected by targets at the transducers in homogenous backgrounds, and uses the MUSIC function to image it. Lumerical FDTD solution is used to model the transducers and the objects to process its response matrix data in Matlab. Clear images of metal dielectric properties have been clearly detected. Security management understanding in airports is also discussed to use new scanning technologies such as microwave imaging in the future.The main contribution of this reseach is that microwave was proved to be able to image and detect illegal objects embedded or implanted inside human body

Towards Large-scale Single-shot Millimeter-wave Imaging for Low-cost Security Inspection

Millimeter-wave (MMW) imaging is emerging as a promising technique for safe security inspection. It achieves a delicate balance between imaging resolution, penetrability and human safety, resulting in higher resolution compared to low-frequency microwave, stronger penetrability compared to visible light, and stronger safety compared to X ray. Despite of recent advance in the last decades, the high cost of requisite large-scale antenna array hinders widespread adoption of MMW imaging in practice. To tackle this challenge, we report a large-scale single-shot MMW imaging framework using sparse antenna array, achieving low-cost but high-fidelity security inspection under an interpretable learning scheme. We first collected extensive full-sampled MMW echoes to study the statistical ranking of each element in the large-scale array. These elements are then sampled based on the ranking, building the experimentally optimal sparse sampling strategy that reduces the cost of antenna array by up to one order of magnitude. Additionally, we derived an untrained interpretable learning scheme, which realizes robust and accurate image reconstruction from sparsely sampled echoes. Last, we developed a neural network for automatic object detection, and experimentally demonstrated successful detection of concealed centimeter-sized targets using 10% sparse array, whereas all the other contemporary approaches failed at the same sample sampling ratio. The performance of the reported technique presents higher than 50% superiority over the existing MMW imaging schemes on various metrics including precision, recall, and mAP50. With such strong detection ability and order-of-magnitude cost reduction, we anticipate that this technique provides a practical way for large-scale single-shot MMW imaging, and could advocate its further practical applications

Towards Real-Time Anomaly Detection within X-ray Security Imagery: Self-Supervised Adversarial Training Approach

Automatic threat detection is an increasingly important area in X-ray security imaging since it is critical to aid screening operators to identify concealed threats. Due to the cluttered and occluded nature of X-ray baggage imagery and limited dataset availability, few studies in the literature have systematically evaluated the automated X-ray security screening. This thesis provides an exhaustive evaluation of the use of deep Convolutional Neural Networks (CNN) for the image classification and detection problems posed within the field. The use of transfer learning overcomes the limited availability of the object of interest data examples. A thorough evaluation reveals the superiority of the CNN features over conventional hand-crafted features. Further experimentation also demonstrates the capability of the supervised deep object detection techniques as object localization strategies within cluttered X-ray security imagery. By addressing the limitations of the current X-ray datasets such as annotation and class-imbalance, the thesis subsequently transitions the scope to- wards deep unsupervised techniques for the detection of anomalies based on the training on normal (benign) X-ray samples only. The proposed anomaly detection models within the thesis employ a conditional encoder-decoder generative adversarial network that jointly learns the generation of high-dimensional image space and the inference of latent space — minimizing the distance between these images and the latent vectors during training aids in learning the data distribution for the normal samples. As a result, a larger distance metric from this learned data distribution at inference time is indicative of an outlier from that distribution — an anomaly. Experimentation over several benchmark datasets, from varying domains, shows the model efficacy and superiority over previous state-of-the-art approaches. Based on the current approaches and open problems in deep learning, the thesis finally provides discussion and future directions for X-ray security imagery

Intelligent optimisation system for airport operation: Hajj Terminal in Saudi Arabia

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.Airport operation level of service (LOS) and performance management are among the major concerns by any airport authority. Two aspects considered in that kind of measurement: passengers prospective and operators prospective. This thesis tries to combine both in its produced optimisation system. This study was carried out in the Hajj terminal of the King Abdul-Aziz international airport and classified the processing time among the most important measures affecting the users’ observation of the level of service. Produced survey has helped to generate performance measure upon passengers prospective. On the other hand a simulation model of the process flow is utilised to formulate driven data model of the terminal process flow operations. The model built on Arena software and correlation study is made from the multiple “what if” scenarios of the model. Then a linear regression is used to generate a model for each variable. Levenberg–Marquardt (LM) algorithm is used after to carry out better regression model then Neuro-Fuzzy (NF) model found to be more efficient as it is picked and used to generate a best observed prediction. The system is optimised through the generated Neuro-Fuzzy (NF) logic model using both Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). A validation in addition to the testing made in the optimisation system. Analysis shows a great deal of improvement in predictions using fuzzy logic instead of linear regression for all dependent variables. PSO and GA optimisations are carried out and compared to the actual results gathered from the Arena simulation report