Improving customer experience while ensuring data privacy for intelligent mobility
Improving customer experience while ensuring data privacy for intelligent mobility
批准号:
EP/N028295/1
负责人:
Helen Eleri Treharne
金额:
$46.42万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --
中文摘要
拟议的研究将计算机科学解决方案应用于以最终用户为中心的挑战。面临的挑战是,如何通过对单个旅行者的详细了解,在保护其数据隐私的同时,在旅行中实现增强的客户体验。除了开发数据隐私的技术解决方案外,该项目还旨在通过开发评估框架来鼓励乘客提供这些数据,以增强他们对数据使用方式和如何控制数据的理解,从而最大限度地提高对服务的信任。目前,这样的框架并不存在,这阻碍了个人数据共享带来的机会,即大多数运输客户出于隐私考虑不愿共享个人数据。研究结果将适用于一系列的旅行模式,但这里的重点将是铁路旅行。通过与铁路运营公司协会(ATOC)和铁路安全与标准委员会(RSSB)的合作,该项目与铁路行业密切合作。近年来,铁路行业在时刻表、中断和向乘客提供实时服务方面的数据可用性显著增加。目前几乎没有个人客户信息,但通过智能手机和其他移动设备,这越来越有可能,随着智能卡和非接触式技术的引入,这将变得更加普遍。该行业的铁路技术战略旨在使铁路成为客户首选的可靠、易用和可感知价值的运输方式。通过乘客的位置、计划、流动性或行李限制,或他们在火车上的位置等信息,增加对乘客的了解,将使服务更加个性化,体验得到改善。挑战在于向客户保证他们的数据得到了适当的保护和使用,并且他们完全掌握了控制权。为该项目组建的联盟汇集了解决这一挑战所需的三个学科:计算机科学,开发框架和技术解决方案(萨里大学和伦敦大学皇家霍洛威大学);人为因素,以开发用例,评估乘客的看法并确保可用的解决方案(拉夫堡大学)和运输系统,以了解要集成的数据流(南安普顿大学)。为了确保解决方案与行业共同创造,并有直接的影响途径,ATOC和RSSB作为利益相关者和项目外部咨询委员会的关键角色,与其他行业专家一起,如EnableID(物联网和个人数据),Transport Systems Catapult(英国政府的智能移动知识交流创新中心)和ThalesUK(铁路技术)。目标是开发一个以统计分析、数据来源和移动技术为基础的隐私评估框架。该框架将与铁路行业正在开发的新兴数据系统集成,也将集成到数字弹射器(英国政府的数字技术创新中心)提出的更广泛的(独立于部门的)框架中。这将使乘客能够更好地沟通,了解为什么需要他们的数据,以及如何处理这些数据,以增加信任和控制感,从而提供数据的良性循环,从而提高客户体验,从而进一步提供数据。
英文摘要
The proposed research applies computer science solutions to an end-user-focussed challenge. The challenge is how to achieve an enhanced customer experience during a journey, through detailed knowledge of an individual traveller, whilst protecting the privacy of their data. As well as developing technical solutions to data privacy, this project aims to encourage passengers to provide this data by developing an evaluation framework to enhance their understanding of how it is used and how they can control it, thus maximising trust in the service. Currently, such a framework does not exist and this is an impediment to the opportunities offered by increased sharing of personal data, i.e. transport customers are, in the majority, unwilling to share personal data due to privacy concerns. The research findings will be applicable to a range of journey modes but the focus here will be on rail travel.The project has been developed closely with the rail industry through partnership with the Association of Train Operating Companies (ATOC) and the Rail Safety and Standards Board (RSSB). In recent years, the availability of data in the rail industry has increased significantly in terms of timetabling, disruption and real-time provision to passengers. Currently there is little in the way of individual customer information but this is increasingly possible through smartphones and other mobile devices and will become more prevalent with the introduction of smartcards and contactless technologies. The industry's Rail Technical Strategy aims to establish rail as customers' preferred form of transport for reliability, ease of use and perceived value. Increased understanding of passengers through information such as their location, their plans, their mobility or luggage limitations, or where they are on the train would enable a more personalised service and an improved experience. The challenge is to assure customers that their data is being protected and used appropriately and that they are fully in control.The consortium assembled for this project brings together the three academic disciplines required to solve this challenge: computer science, to develop the framework and technical solutions (University of Surrey and Royal Holloway, University of London); human factors, to develop the use cases, evaluate passenger perceptions and ensure usable solutions (Loughborough University) and transport systems to bring understanding of the data streams to be integrated (University of Southampton). To ensure the solutions are co-created with the industry and have a direct pathway to impact, ATOC and RSSB have a key role as stakeholders and on the project's External Advisory board, alongside other sector experts such as EnableID (Internet of Things and personal data), the Transport Systems Catapult (the UK government's innovation centre for intelligent mobility knowledge exchange) and ThalesUK (rail technology).The objective is to develop a privacy evaluation framework underpinned by statistical analysis, data provenance and mobile technology. This framework will be integrated with emerging data systems being developed by the rail industry and also into a wider (sector-independent) framework being proposed by the Digital Catapult (the UK government's innovation centre for digital technologies). This will enable better communication to passengers as to why their data is needed and how it will be handled in order to increase trust and feelings of control, thus providing a virtuous circle of data provision, leading to enhanced customer experience and hence further data provision.
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Consumer Centric Data Control, Tracking and Transparency - A Position Paper
以消费者为中心的数据控制、跟踪和透明度 - 立场文件
DOI:
10.1109/trustcom/bigdatase.2018.00191
发表时间:
2018
期刊:
影响因子:
--
作者:
[Tapsell J]
通讯作者:
Tapsell J
DOI:
10.1109/trustcom/bigdatase.2018.00185
发表时间:
2018-05
期刊:
2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
影响因子:
--
作者:
[Freya Sheer Hardwick;Raja Naeem Akram;K. Markantonakis]
通讯作者:
Freya Sheer Hardwick;Raja Naeem Akram;K. Markantonakis
Extensive Security Verification of the LoRaWAN Key-Establishment: Insecurities & Patches
LoRaWAN 密钥建立的广泛安全验证:不安全性
DOI:
10.1109/eurosp48549.2020.00034
发表时间:
2020
期刊:
影响因子:
--
作者:
[Wesemeyer S]
通讯作者:
Wesemeyer S
DOI:
10.1016/j.future.2017.11.026
发表时间:
2018-03
期刊:
Future Gener. Comput. Syst.
影响因子:
--
作者:
[Raja Naeem Akram;Hsiao-Hwa Chen;Javier López;D. Sauveron;L. Yang]
通讯作者:
Raja Naeem Akram;Hsiao-Hwa Chen;Javier López;D. Sauveron;L. Yang
Anonymous Single Sign-on with Proxy Re-Verification
带有代理重新验证的匿名单点登录
DOI:
10.48550/arxiv.1811.07642
发表时间:
2018
期刊:
影响因子:
--
作者:
[Han J]
通讯作者:
Han J
共 9 条
国内基金
海外基金
电商“顾客直连制造”(customer to manufacturer,电商C2M)模式供应链决策——基于博弈模型的研究
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批准号:72171051
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项目类别:面上项目
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资助金额:48.00万元
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批准年份:2021
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负责人:杨柳
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依托单位:
电商“顾客直连制造”(customer to manufacturer, 电商C2M)模式供应链决策——基于博弈模型的研究
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批准号:--
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项目类别:--
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资助金额:48万元
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批准年份:2021
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负责人:杨柳
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依托单位: