Real-World Smartphone-based Gait Recognition

As the smartphone and the services it provides are becoming targets of cybercrime, it is critical to secure smartphones. However, it is important security controls are designed to provide continuous and user-friendly security. Amongst the most important of these is user authentication, where users have experienced a significant rise in the need to authenticate to the device and individually to the numerous apps that it contains. Gait authentication has gained attention as a mean of non-intrusive or transparent authentication on mobile devices, capturing the information required to verify the authenticity of the user whilst the person is walking. Whilst prior research in this field has shown promise with good levels of recognition performance, the results are constrained by the gait datasets utilised being based upon highly controlled laboratory-based experiments which lack the variability of real-life environments. This paper introduces an advanced real-world smartphone-based gait recognition system that recognises the subject within real-world unconstrained environments. The proposed model is applied to the uncontrolled gait dataset, which consists of 44 users over a 7–10 day capture – where users were merely asked to go about their daily activities. No conditions, controls or expectations of particular activities were placed upon the participants. The experiment has modelled four types of motion normal walking, fast walking and down and upstairs for each of the users. The evaluation of the proposed model has achieved an equal error rate of 11.38%, 11.32%, 24.52%, 27.33% and 15.08% for the normal, fast, down and upstairs and all activities respectively. The results illustrate, within an appropriate framework, that gait recognition is a viable technique for real-world use

Continuous Authentication of Users to Robotic Technologies Using Behavioural Biometrics

Collaborative robots and current human–robot interaction systems, such as exoskeletons and teleoperation, are key technologies with profiles that make them likely security targets. Without sufficient protection, these robotics technologies might become dangerous tools that are capable of causing damage to their environments, increasing defects in work pieces and harming human co-workers. As robotics is a critical component of the current automation drive in many advanced economies, there may be serious economic effects if robot security is not appropriately handled. The development of suitable security for robots, particularly in industrial contexts, is critical. Collaborative robots, exoskeletons and teleoperation are all examples of robotics technologies that might need close collaboration with humans, and these interactions must be appropriately protected. There is a need to guard against both external hackers (as with many industrial systems) and insider malfeasance. Only authorised users should be able to access robots, and they should use only those services and capabilities they are qualified to access (e.g. those for which they are appropriately cleared and trained). Authentication is therefore a crucial enabling mechanism. Robot interaction will largely be ongoing, so continuous rather than one-time authentication is required. In robot contexts, continuous biometrics can be used to provide effective and practical authentication of individuals to robots. In particular, the working behaviour of human co-workers as they interact with robots can be used as a means of biometric authentication. This thesis demonstrates how continuous biometric authentication can be used in three different environments: a direct physical manipulation application, a sensor glove application and a remote access application. We show how information acquired from the collaborative robot's internal sensors, wearable sensors (similar to those found in an exoskeleton), and teleoperated robot control and programming can be harnessed to provide appropriate authentication. Thus, all authentication uses data that are collected or generated as part of the co-worker simply going about their work. No additional action is needed. For manufacturing environments, this lack of intrusiveness is an important feature. The results presented in this thesis show that our approaches can discriminate appropriately between users. We believe that our machine learning-based approaches can provide reasonable and practical solutions for continually authenticating users to robots in many environments, particularly in manufacturing contexts

Facilitating free travel in the Schengen area - A position paper by the European Association for Biometrics

Due to migration, terror‐threats and the viral pandemic, various EU member states have re‐established internal border control or even closed their borders. European Association for Biometrics (EAB), a non‐profit organisation, solicited the views of its members on ways which biometric technologies and services may be used to help with re‐establishing open borders within the Schengen area while at the same time mitigating any adverse effects. From the responses received, this position paper was composed to identify ideas to re‐establish free travel between the member states in the Schengen area. The paper covers the contending needs for security, open borders and fundamental rights as well as legal constraints that any technological solution must consider. A range of specific technologies for direct biometric recognition alongside complementary measures are outlined. The interrelated issues of ethical and societal considerations are also highlighted. Provided a holistic approach is adopted, it may be possible to reach a more optimal trade‐off with regards to open borders while maintaining a high‐level of security and protection of fundamental rights. European Association for Biometrics and its members can play an important role in fostering a shared understanding of security and mobility challenges and their solutions

Biometric Systems Interaction Assessment: The State of the Art

The design and implementation of effective and efficient biometric systems presents a series of challenges to information technology (IT) designers to ensure robust performance. One of the most important factors across biometric systems, aside from algorithmic matching ability, is the human interaction influence on performance. Changes in biometric system paradigms have motivated further testing methods, especially within mobile environments, where the interaction with the device has fewer environmental constraints, whichmay severely affect system performance. Testing methods involve the need for reflecting on the influence of user-system interaction on the overall system performance in order to provide information for design and testing. This paper reflects on the state of the art of biometric systems interaction assessment, leading to a comprehensive document of the relevant research and standards in this area. Furthermore, the current challenges are discussed and thus we provide a roadmap for the future of biometrics systems interaction research

Device profiling analysis in Device-Aware Network

As more and more devices with a variety of capabilities are Internet-capable, device independence becomes a big issue when we would like the information that we request to be correctly displayed. This thesis introduces and compares how existing standards create a profile that describes the device capabilities to achieve the goal of device independence. After acknowledging the importance of device independence, this paper utilizes the idea to introduce a Device-Aware Network (DAN). DAN provides the infrastructure support for device-content compatibility matching for data transmission. We identify the major components of the DAN architecture and issues associated with providing this new network service. A Device-Aware Network will improve the network's efficiency by preventing unusable data from consuming host and network resources. The device profile is the key issue to achieve this goal.http://archive.org/details/deviceprofilingn109451301Captain, Taiwan ArmyApproved for public release; distribution is unlimited

The Application of the Human-Biometric Sensor Interaction Method to Automated Border Control Systems

Biometrics components are used in many different systems and technologies to verify that the user is whom they say they are. In Automated Border Control systems, biometrics components used in conjunction with a traveller's documents to make sure the user is whom they say they are so that they can cross into a countries borders. The systems are expected to verify the identity with a higher degree than officers who manually check travellers. Each year the number of travellers crossing through a country borders increases and so systems are expected to handle bigger demands; through improving the user experience to ensuring accuracy and performance standards increase. While the system does bring its benefits through increased speed and higher security, there are drawbacks. One of the main issues with the systems is a lack of standardisation across implementations. Passing through an automated process at Heathrow may be different to Hong Kong. The infrastructure, information, environment and guidance given during the transaction will all greatly differ for the user. Furthermore, the individual components and subsequent processing will be evaluated using a different methodology too. This thesis reports on the contrasts between implementations, looking at solutions which utilise different biometric modalities and travel documents. Several models are devised to establish a process map which can be applied to all systems. Investigating further, a framework is described for a novel assessment method to evaluate the performance of a system. An RGB-D sensor is implemented, to track and locate the user within an interactive environment. By doing so, the user's interaction is assessed in real-time. Studies then report on the effectiveness of the solution within a replicated border control scenario. Several relationships are studied to improve the technologies used within the scenario. Successful implementation of the automated assessment method may improve the user's experience with systems, improving information and guidance, increasing the likelihood of successful interaction while maintaining a high level of security and quicker processing times

Privacy-aware Biometric Blockchain based e-Passport System for Automatic Border Control

In the middle of 1990s, World Wide Web technology initially steps into our life. Now, 30 years after that, widespread internet access and established computing technology bring embodied real life into Metaverse by digital twin. Internet is not only blurring the concept of physical distance, but also blurring the edge between the real and virtual world. Another breakthrough in computing is the blockchain, which shifts the root of trust attached to a system administrator to the computational power of the system. Furthermore, its favourable properties such as immutable time-stamped transaction history and atomic smart contracts trigger the development of decentralized autonomous organizations (DAOs). Combining above two, this thesis presents a privacy-aware biometric Blockchain based e-passport system for automatic border control(ABC), which aims for improving the efficiency of existing ABC system. Specifically, through constructing a border control Metaverse DAO, border control workload can be autonomously self-executed by atomic smart contracts as transaction and then immutably recorded on Blockchain. What is more, to digitize border crossing documentation, biometric Blockchain based e-passport system(BBCVID) is created to generate an immutable real-world identity digital twin in the border control Metaverse DAO through Blockchain and biometric identity authentication. That is to say, by digitizing border crossing documentation and automatizing both biometric identity authentication and border crossing documentation verification, our proposal is able to significantly improve existing border control efficiency. Through system simulation and performance evaluation by Hyperledger Caliper, the proposed system turns out to be able to improve existing border control efficiency by 3.5 times more on average, which is remarkable. What is more, the dynamic digital twin constructed by BBCVID enables computing techniques such as machine learning and big data analysis applicable to real-world entity, which has a huge potential to create more value by constructing smarter ABC systems