PRIvacy-aware personal data management and Value Enhancement for Leisure Travellers (PriVELT)

注重隐私的个人数据管理和休闲旅行者的价值提升 (PriVELT)

• 批准号: EP/R033749/1
• 负责人: Shujun Li
• 金额: $ 54.67万
• 依托单位: University of Kent
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR033749%2F1
• 关键词: PRIvacy; aware; personal; data; management

The consumption of a seamless travel experience requires travellers to share their personal data with numerous individual travel and tourism service providers. There is a general lack of guidelines on how travellers should manage their data sharing activities while travelling, which lead to two unwanted situations: 1) travellers simply share their data without understanding the privacy and security risks and consequences; 2) travellers become over-worried about such risks so that they stop sharing data, which reduce their overall travel experience and prevent organisations to provide better (more personalised) services. The wide spectrum of data sharing with many entities including on social media, instant messaging and other online social platforms makes the situations worse as travellers often cannot see a big picture of how they have shared their data in the past to adapt their data sharing behaviour.PriVELT will address the two-sided challenges associated with offering a seamless and highly personalised end-to-end travel experience while balancing the privacy and security needs of leisure travellers. On the one hand, travel service providers need to identify effective ways to incentivise travellers to share personal data in exchange of tangible benefits such as higher quality service, personalised offers, discounts, or add-on services. On the other hand, travellers need to better manage the sharing of their personal data to minimise privacy-related risks while optimising value from a seamless travel experience. Therefore, PriVELT aims to develop an innovative user-centric and privacy-aware digital platform that will empower leisure travellers to better manage the sharing of their personal data with travel service providers and other entities and foster new business opportunities for the travel and tourism industry through encouraging better (more transparent and effective) usage of travellers' data.PriVELT will develop the user-centric platform based on a holistic socio-technical framework of privacy-related traveller behaviour. The framework will provide intervention points to effectively nudge travellers to share their personal data more responsibly. PriVELT draws from theories in social sciences, including consumer psychology and behavioural economics, to better explain how consumers make decisions to disclose personal information in exchange for values. PriVELT also considers travellers' psychological limitation, such as limited understanding of privacy risks, which may induce irrational behaviour in privacy-related decision-making process while traveling.In order to achieve its aim, PriVELT's research will be interdisciplinary, co-created, theory-informed, evidence-based, user-centric, and real world-facing. PriVELT will combine both social and technical methods to collect and analyse data, integrating focus groups and interviews with relevant stakeholders, a panel survey, lab-based user studies, and field studies with real domestic and international travellers (end users) to identify and apply an array of effective nudging strategies to inform travellers with risks and consequences of sharing personal data while traveling.One of the key outcomes will be a digital platform that will be used for: 1) monitoring travellers' data sharing activities; 2) enhancing situational awareness of privacy risks related to data shared; 3) providing an innovative way of achieving dynamic consent management for participants, allowing dynamic updating of the consent while travelling; ; 4) providing better recommendations for travellers to adapt their data sharing behaviours. The digital platform will be composed of three main components: 1) tools at the traveller (user/client) side in the form of a mobile app, 2) an infrastructure and tools at the server side for anonymised data aggregation and analytics purposes, and 3) the API and user interfaces for consumers of data shared by travellers.

无缝旅行体验的消费要求旅行者与许多个人旅行和旅游服务提供商共享其个人数据。普遍缺乏关于旅行者在旅行时如何管理其数据共享活动的准则，这导致了两种不必要的情况：1）旅行者只是在不了解隐私风险和后果的情况下共享数据； 2）旅行者对这种风险变得过于责任，以便他们停止共享数据，从而降低其整体旅行经验并防止组织提供更好（更个性化的）服务。与许多实体（包括在社交媒体上，即时消息传递和其他在线社交平台上）的广泛数据共享使情况变得更糟，因为旅行者经常看不到他们过去如何共享数据以适应其数据共享行为的全局。私人将解决与提供无缝且高度个性化的最终旅行的两面挑战，并在提供的范围内保持良好的旅行，并在安全性的过程中保持安全性和安全性，并在安全方面保持良好的范围。一方面，旅行服务提供商需要确定有效的方法来激励旅行者共享个人数据，以交换有形的福利，例如高质量的服务，个性化的优惠，折扣或附加服务。另一方面，旅行者需要更好地管理其个人数据的共享，以最大程度地降低与隐私相关的风险，同时优化无缝旅行体验的价值。 Therefore, PriVELT aims to develop an innovative user-centric and privacy-aware digital platform that will empower leisure travellers to better manage the sharing of their personal data with travel service providers and other entities and foster new business opportunities for the travel and tourism industry through encouraging better (more transparent and effective) usage of travellers' data.PriVELT will develop the user-centric platform based on a holistic socio-technical framework of privacy-related traveller 行为。该框架将提供干预点，以有效地推动旅行者，以更负责任地共享其个人数据。 Privelt从社会科学理论（包括消费者心理学和行为经济学）中汲取灵感，以更好地解释消费者如何做出决定以披露个人信息以换取价值。 Privelt还考虑了旅行者的心理局限性，例如对隐私风险的了解有限，这可能会在旅行时引起与隐私相关的决策过程中的非理性行为。为了实现其目标，Privelt的研究将是跨学科的，共同创造的，理论，理论上的，证据，基于证据，用户储备，估计和现实的世界。 Privelt将结合社会和技术方法来收集和分析数据，将焦点小组和与相关利益相关者的访谈整合，小组调查，基于实验室的用户研究以及与真正的国内和国际旅行者（最终用户）（最终用户）（最终用户）识别和应用一系列有效的裸露策略，以识别和应用一系列有效的裸露策略，以供您进行旅行的风险和后果。 活动; 2）增强与共享数据有关的隐私风险的情境意识； 3）提供一种创新的方式来为参与者实现动态同意管理，从而在旅行时允许对同意的动态更新； ; 4）为旅行者提供更好的建议，以调整其数据共享行为。数字平台将由三个主要组成部分组成：1）移动应用程序形式的旅行者（用户/客户端）的工具，2）服务器端的基础架构和工具，用于匿名数据聚合和分析目的，以及3）API和用户界面，用于旅行者共享数据的消费者。

项目成果

Tension between GDPR and Public Blockchains: A Data-Driven Analysis of Online Discussions

GDPR 与公共区块链之间的紧张关系：在线讨论的数据驱动分析

• DOI: 10.1145/3433174.3433587
• 发表时间: 2020
• 作者: Chousein Z

Crime scripting: A systematic review

• DOI: 10.1177/1477370819850943
• 发表时间: 2021-07-01
• 期刊: EUROPEAN JOURNAL OF CRIMINOLOGY
• 影响因子: 1.9
• 作者: Dehghanniri, Hashem;Borrion, Herve
• 通讯作者: Borrion, Herve

All about uncertainties and traps: Statistical oracle-based attacks on a new CAPTCHA protection against oracle attacks

关于不确定性和陷阱：基于统计预言机的攻击，针对新的验证码防范预言机攻击

• DOI: 10.1016/j.cose.2020.101758
• 发表时间: 2020
• 期刊: Computers & Security
• 影响因子: 5.6
• 作者: Hernández-Castro C

A Data-Driven Analysis of Blockchain Systems' Public Online Communications on GDPR

基于 GDPR 的区块链系统公共在线通信的数据驱动分析

• DOI: 10.1109/dapps49028.2020.00003
• 发表时间: 2020
• 作者: Belen Saglam R

Privacy nudges for disclosure of personal information: A systematic literature review and meta-analysis.

• DOI: 10.1371/journal.pone.0256822
• 发表时间: 2021
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Ioannou A;Tussyadiah I;Miller G;Li S;Weick M
• 通讯作者: Weick M