A Decentralised Digital Token Architecture for Public Transport

• URL: http://arxiv.org/abs/2012.01382v3
• Date: Mon, 22 Jul 2024 06:40:40 GMT
• Title: A Decentralised Digital Token Architecture for Public Transport
• Authors: Oscar King, Geoffrey Goodell,
• Abstract summary: This work aims to motivate the need and establish the feasibility of the application of a privacy-enhancing digital token management service to public transit. A proof-of-concept implementation is developed, building upon a design proposed by Goodell and Aste. The demonstrated throughput and latency indicate that the system can feasibly compete with solutions currently in use.
• Score: 1.2277343096128712
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Digitisation is often viewed as beneficial to a user. Whereas traditionally, people would physically have to identify to a service, pay for a ticket in cash, or go into a library to access a book, people can now achieve all of this through a click of a button. Such actions may seem functionally identical to their analogue counterparts, but in the digital case, a user's actions are automatically recorded. The recording of user's interactions presents a problem because once the information is collected, it is outside of the control of the person whom it concerns. This issue is only exacerbated by the centralisation of the authentication mechanisms underpinning the aforementioned services, permitting the aggregation and analysis of even more data. This work aims to motivate the need and establish the feasibility of the application of a privacy-enhancing digital token management service to public transit. A proof-of-concept implementation is developed, building upon a design proposed by Goodell and Aste. This implementation was optimised for the public transport use case. Its performance is tested in a local environment to better understand the technical challenges and assess the technical feasibility of the system in a production setting. It was observed that for loads between one and five requests per second the proof-of-concept performs comparably to other contactless payment systems, with a maximum median response time less than two seconds. Due to hardware bottlenecks, reliable throughput in our test environment was limited to five requests per second. The demonstrated throughput and latency indicate that the system can feasibly compete with solutions currently in use. Yet, further work is needed to demonstrate their performance characteristics in an environment similar to that experienced in production.

Related papers

• Benchmarking the performance of a self-custody, non-ledger-based, obliviously managed digital payment system [1.2277343096128712]
  This paper advances an existing retail CBDC framework developed at University College London. Our proposed design allows users to retain direct custody of their assets without the need for intermediary service providers. In parallel, we introduce a streamlined Digital Ledger designed to offer fast, immutable, and decentralized transaction validation.
  arXiv  Detail & Related papers  (2024-04-19T11:57:32Z)
• Leveraging Machine Learning for Wi-Fi-based Environmental Continuous Two-Factor Authentication [0.44998333629984877]
  We present a novel 2FA approach replacing the user's input with decisions made by Machine Learning (ML) Our system exploits unique environmental features associated with the user, such as beacon frame characteristics and Received Signal Strength Indicator ( RSSI) values from Wi-Fi Access Points (APs) For enhanced security, our system mandates that the user's two devices (i.e., a login device and a mobile device) be situated within a predetermined proximity before granting access.
  arXiv  Detail & Related papers  (2024-01-12T14:58:15Z)
• Agile gesture recognition for capacitive sensing devices: adapting on-the-job [55.40855017016652]
  We demonstrate a hand gesture recognition system that uses signals from capacitive sensors embedded into the etee hand controller. The controller generates real-time signals from each of the wearer five fingers. We use a machine learning technique to analyse the time series signals and identify three features that can represent 5 fingers within 500 ms.
  arXiv  Detail & Related papers  (2023-05-12T17:24:02Z)
• Certified Hardware Requirements Undermine Digital Currency [0.0]
  This article critically assesses the problems that digital currency solutions are being proposed to solve. We examine the characteristics of trusted computing within the context of its application to digital currency systems. We conclude that the interests of consumers would be better served by design approaches to digital currency that do not require the use of trusted hardware.
  arXiv  Detail & Related papers  (2022-09-24T19:42:11Z)
• Concepts and Algorithms for Agent-based Decentralized and Integrated Scheduling of Production and Auxiliary Processes [78.120734120667]
  This paper describes an agent-based decentralized and integrated scheduling approach. Part of the requirements is to develop a linearly scaling communication architecture. The approach is explained using an example based on industrial requirements.
  arXiv  Detail & Related papers  (2022-05-06T18:44:29Z)
• Benchmarking high-fidelity pedestrian tracking systems for research, real-time monitoring and crowd control [55.41644538483948]
  High-fidelity pedestrian tracking in real-life conditions has been an important tool in fundamental crowd dynamics research. As this technology advances, it is becoming increasingly useful also in society. To successfully employ pedestrian tracking techniques in research and technology, it is crucial to validate and benchmark them for accuracy. We present and discuss a benchmark suite, towards an open standard in the community, for privacy-respectful pedestrian tracking techniques.
  arXiv  Detail & Related papers  (2021-08-26T11:45:26Z)
• Estimating the Robustness of Public Transport Systems Using Machine Learning [62.997667081978825]
  Planning public transport systems is a highly complex process involving many steps. Integrating robustness from a passenger's point of view makes the task even more challenging. In this paper, we explore a new way of such a scenario-based robustness approximation by using methods from machine learning.
  arXiv  Detail & Related papers  (2021-06-10T05:52:56Z)
• Digital Twins: State of the Art Theory and Practice, Challenges, and Open Research Questions [62.67593386796497]
  This work explores the various DT features and current approaches, the shortcomings and reasons behind the delay in the implementation and adoption of digital twin. The major reasons for this delay are the lack of a universal reference framework, domain dependence, security concerns of shared data, reliance of digital twin on other technologies, and lack of quantitative metrics.
  arXiv  Detail & Related papers  (2020-11-02T19:08:49Z)
• Assisted Perception: Optimizing Observations to Communicate State [112.40598205054994]
  We aim to help users estimate the state of the world in tasks like robotic teleoperation and navigation with visual impairments. We synthesize new observations that lead to more accurate internal state estimates when processed by the user.
  arXiv  Detail & Related papers  (2020-08-06T19:08:05Z)
• Predictability and Fairness in Social Sensing [6.457260875902829]
  We consider the design of distributed algorithms that govern the manner in which agents contribute to a social sensing platform. We show how the IFS framework can be used to realise systems that deliver a predictable quality of service to agents.
  arXiv  Detail & Related papers  (2020-07-31T15:04:08Z)
• A general anomaly detection framework for fleet-based condition monitoring of machines [16.51849885526826]
  Machine failures decrease up-time and can lead to extra repair costs or even to human casualties and environmental pollution. Recent condition monitoring techniques use artificial intelligence in an effort to avoid time-consuming manual analysis and handcrafted feature extraction. This work proposes an unsupervised, generic, anomaly detection framework for fleet-based condition monitoring.
  arXiv  Detail & Related papers  (2019-12-30T14:35:45Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.