Databox: Privacy-Aware Infrastructure for Managing Personal Data
Lead Research Organisation:
Queen Mary University of London
Department Name: Sch of Electronic Eng & Computer Science
Abstract
Building privacy, trust and security into the evolving digital ecosystem is broadly recognized as a key societal challenge. Regulatory activities in the US, Europe and Japan are complemented by industry initiatives that seek to rebalance "the crisis in trust" occasioned by widespread personal data harvesting. All parties agree that key to this challenge are increased accountability and control. Accountability not only seeks to strengthen compliance but also make the emerging ecosystem more transparent to consumers, while control seeks to empower consumers and provide them with the means of actively exercising choice. This proposal will develop the underlying technology infrastructure required to deliver both accountability and control.
Although personal data management is generally considered an intensely personal matter, it is also inherently social: it is impractical to withdraw from all online activity simply to protect one's privacy. The success of the modern Internet and the "free" services it supports largely rests on the ability for advertisers and analytics providers to make money with the result that approaches that remove or diminish advertising revenues have been doomed to failure. The many motivations and uses for systems enabling personal management of personal data point to a need for tools enabling individuals to take more explicit control over the collection and usage of their data and the information inferred from their online activities, while addressing the challenges of HDI.
Working with partner organisations we have refined our vision of just such a tool, a Databox, an on-demand personal data aggregation and query point, control over which rests directly with the user. The Databox vision is of an open-source personal networked device augmented by cloud-hosted services that collates, curates, and mediates access to our personal data. The Databox will enable and, in some cases, may even host third party applications and services that process personal data. The Databox will form the heart of an individual's personal data processing ecosystem, providing a platform for managing secure access to these data and enabling authorised third parties to provide the owner with authenticated services while roaming outside the home environment.
Although personal data management is generally considered an intensely personal matter, it is also inherently social: it is impractical to withdraw from all online activity simply to protect one's privacy. The success of the modern Internet and the "free" services it supports largely rests on the ability for advertisers and analytics providers to make money with the result that approaches that remove or diminish advertising revenues have been doomed to failure. The many motivations and uses for systems enabling personal management of personal data point to a need for tools enabling individuals to take more explicit control over the collection and usage of their data and the information inferred from their online activities, while addressing the challenges of HDI.
Working with partner organisations we have refined our vision of just such a tool, a Databox, an on-demand personal data aggregation and query point, control over which rests directly with the user. The Databox vision is of an open-source personal networked device augmented by cloud-hosted services that collates, curates, and mediates access to our personal data. The Databox will enable and, in some cases, may even host third party applications and services that process personal data. The Databox will form the heart of an individual's personal data processing ecosystem, providing a platform for managing secure access to these data and enabling authorised third parties to provide the owner with authenticated services while roaming outside the home environment.
Planned Impact
The proposed research will benefit society through numerous pathways: industry, academia, and through several user communities including open-source developers, Internet advocacy groups, and engagement in the many live policy and other debates currently active in the personal data space. Fundamentally however, realisation of the Databox as an open-source platform for the broader community will be of most significant benefit to all citizens. The combination of infrastructure that enables open source development and drives critical mass, with commercial and policy impact opportunities via our industrial and advocacy partners will add significant momentum to the growing community of HDI practitioners.
Perhaps the most critical pathway to impact is the Databox itself. Databox is a practical open-source platform whose methodology entails deployment of working artefacts with users. These artefacts will create a comprehensive software platform that enables trusted service-to-user solutions across multiple market segments. These software tools will realise various advantages to individuals for better control over their personal data, digital identity and privacy. This provides more possibilities of access to personal data for third party applications, generating new businesses and differentiating their products with innovative services.
There are a number of other impact channels:
- The Emerging HDI Community http:// hdiresearch.org
- The Open Source Development Community
- Industry
- Advocacy Groups
- Broader Society
- Academics
Full details of the engagement plans are presented in the attached Pathways to Impact document.
Perhaps the most critical pathway to impact is the Databox itself. Databox is a practical open-source platform whose methodology entails deployment of working artefacts with users. These artefacts will create a comprehensive software platform that enables trusted service-to-user solutions across multiple market segments. These software tools will realise various advantages to individuals for better control over their personal data, digital identity and privacy. This provides more possibilities of access to personal data for third party applications, generating new businesses and differentiating their products with innovative services.
There are a number of other impact channels:
- The Emerging HDI Community http:// hdiresearch.org
- The Open Source Development Community
- Industry
- Advocacy Groups
- Broader Society
- Academics
Full details of the engagement plans are presented in the attached Pathways to Impact document.
Organisations
- Queen Mary University of London (Lead Research Organisation)
- BT Group (Collaboration)
- Telefonica S.A (Collaboration)
- British Broadcasting Corporation (BBC) (Collaboration)
- University of Cambridge (Project Partner)
- Telefónica (Spain) (Project Partner)
- HORIZON Digital Economy Research (Project Partner)
- Microsoft Research (United Kingdom) (Project Partner)
- British Broadcasting Corporation (United Kingdom) (Project Partner)
- Internet Society (Project Partner)
- Cornell University (Project Partner)
- BT Group (United Kingdom) (Project Partner)
Publications
Moore J
(2019)
Zest: REST over ZeroMQ
Chen J
(2020)
Who is responsible for data processing in smart homes? Reconsidering joint controllership and the household exemption
in International Data Privacy Law
Nilsson T
(2020)
Visions, Values, and Videos
Perera C
(2017)
Valorising the IoT Databox : creating value for everyone Valorising the IoT Databox : creating value for everyone
in Transactions on Emerging Telecommunications Technologies
Tolmie P
(2017)
The practical politics of sharing personal data
in Personal and Ubiquitous Computing
Sailaja N
(2019)
The Living Room of the Future
Sailaja N
(2019)
The Living Room of the Future
Mortier R
(2017)
The Encyclopedia of Human-Computer Interaction
Kilic D
(2021)
The cardboard box study: understanding collaborative data management in the connected home
in Personal and Ubiquitous Computing
Chamberlain A
(2017)
Special theme on privacy and the Internet of things
in Personal and Ubiquitous Computing
| Description | A recent NSF report and a number of security and privacy disasters in the IoT space (see the blog post on Schneier's blog) highlighted the challenges and opportunities in Edge Computing, leveraging the high processing capabilities and low latency offered at the edge of the network (IoT devices, smartphones, cloudlets) for achieving scalable yet secure and private analytics. Recently we put a few papers on ArXiv, focusing on Privacy-Preserving Analytics using smartphones and constrained devices on the network (such as a Raspberry Pi and Smartphones). I encourage the privacy, machine learning, and mobile computing enthusiasts to read these papers and kindly provide us with any feedback on the analytics which can improve the research efforts in this space. Seyed Ali Osia, Ali Shahin Shamsabadi, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi, "Privacy-Preserving Deep Inference for Rich User Data on The Cloud", Available on ArXiv, October 2017. Deep neural networks are increasingly being used in a variety of machine learning applications applied to rich user data on the cloud. However, this approach introduces a number of privacy and efficiency challenges, as the cloud operator can perform secondary inferences on the available data. Recently, advances in edge processing have paved the way for more efficient, and private, data processing at the source for simple tasks and lighter models, though they remain a challenge for larger, and more complicated models. In this paper, we present a hybrid approach for breaking down large, complex deep models for cooperative, privacy-preserving analytics. We do this by breaking down the popular deep architectures and fine-tune them in a particular way. We then evaluate the privacy benefits of this approach based on the information exposed to the cloud service. We also asses the local inference cost of different layers on a modern handset for mobile applications. Our evaluations show that by using certain kind of fine-tuning and embedding techniques and at a small processing costs, we can greatly reduce the level of information available to unintended tasks applied to the data feature on the cloud, and hence achieving the desired tradeoff between privacy and performance. Sandra Servia-Rodriguez, Liang Wang, Jianxin R. Zhao, Richard Mortier, Hamed Haddadi, "Personal Model Training under Privacy Constraints", Available on ArXiv, March 2017. Many current Internet services rely on inferences from models trained on user data. Commonly, both the training and inference tasks are carried out using cloud resources fed by personal data collected at scale from users. Holding and using such large collections of personal data in the cloud creates privacy risks to the data subjects, but is currently required for users to benefit from such services. We explore how to provide for model training and inference in a system where computation is moved to the data in preference to moving data to the cloud, obviating many current privacy risks. Specifically, we take an initial model learnt from a small set of users and retrain it locally using data from a single user. We evaluate on two tasks: one supervised learning task, using a neural network to recognise users' current activity from accelerometer traces; and one unsupervised learning task, identifying topics in a large set of documents. In both cases the accuracy is improved. We also demonstrate the feasibility of our approach by presenting a performance evaluation on a representative resource-constrained device (a Raspberry Pi). Seyed Ali Ossia, Ali Shahin Shamsabadi, Ali Taheri, Hamid R. Rabiee, Nic Lane, Hamed Haddadi, "A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics", Available on ArXiv, March 2017. The increasing quality of smartphone cameras and variety of photo editing applications, in addition to the rise in popularity of image-centric social media, have all led to a phenomenal growth in mobile-based photography. Advances in computer vision and machine learning techniques provide a large number of cloud-based services with the ability to provide content analysis, face recognition, and object detection facilities to third parties. These inferences and analytics might come with undesired privacy risks to the individuals. In this paper, we address a fundamental challenge: Can we utilize the local processing capabilities of modern smartphones efficiently to provide desired features to approved analytics services, while protecting against undesired inference attacks and preserving privacy on the cloud? We propose a hybrid architecture for a distributed deep learning model between the smartphone and the cloud. We rely on the Siamese network and machine learning approaches for providing privacy based on defined privacy constraints. We also use transfer learning techniques to evaluate the proposed method. Using the latest deep learning models for Face Recognition, Emotion Detection, and Gender Classification techniques, we demonstrate the effectiveness of our technique in providing highly accurate classification results for the desired analytics, while proving strong privacy guarantees. |
| Exploitation Route | The findings in Edge computing are of direct interest to the computing sector, the privacy enthusiast, and the mobile computing industry. In addition, this is of interest to those developing in the IoT sector (e.g., British Gas, or BT) which need to drive the effort towards secure, private, and efficient ecosystem of services, devices, and applications centred around the users. |
| Sectors | Digital/Communication/Information Technologies (including Software),Energy,Security and Diplomacy |
| URL | https://www.databoxproject.uk |
| Description | The award has lead to the Human-Data Interaction EPSRC NetworkPlus The award has lead to the Defence Against Dark Artefacts EPSRC grant The research has been showcased at Victoria & Albert Museum and Tate by the BBC. |
| First Year Of Impact | 2018 |
| Sector | Creative Economy,Digital/Communication/Information Technologies (including Software),Education |
| Impact Types | Policy & public services |
| Description | Coronavirus Discourses: Linguistic Evidence For Effective Public Health Messaging |
| Amount | £365,126 (GBP) |
| Funding ID | AH/V015125/1 |
| Organisation | Arts & Humanities Research Council (AHRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2021 |
| End | 07/2022 |
| Description | EPSRC Trust, Identity, Privacy, and Security 2 |
| Amount | £1,249,510 (GBP) |
| Funding ID | EP/R03351X/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 07/2018 |
| End | 06/2020 |
| Description | Human Data Interaction: Legibility, Agency, Negotiability |
| Amount | £1,298,811 (GBP) |
| Funding ID | EP/R045178/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 07/2018 |
| End | 06/2021 |
| Description | Microsoft Azure Research Award |
| Amount | $20,000 (USD) |
| Funding ID | CRM:0740917 |
| Organisation | Microsoft Research |
| Department | Microsoft Research Cambridge |
| Sector | Private |
| Country | United Kingdom |
| Start | 01/2018 |
| End | 12/2018 |
| Description | Privacy-preserving personal data analytics on the Databox |
| Amount | £100,000 (GBP) |
| Organisation | Queen Mary University of London |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 01/2017 |
| End | 06/2021 |
| Description | UK Dementia Research Institute |
| Amount | £20,000,000 (GBP) |
| Funding ID | WBDT_P80558 UK-DRI |
| Organisation | Imperial College London |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 07/2019 |
| End | 06/2024 |
| Title | Advanced IoT Testbed |
| Description | Our state of the art IoT Testbed is instrumental to a number of research projects, government regulation reports, TV documentaries, and independent investigations into the security and privacy of smart devices. The testbed consists of over 140 various consumer IoT devices, state of the art network and device performance monitoring (through BatteryLab), and various automation techniques. Through close collaboration with friends at Northeastern University, We also make our testbed configuration and publications' datasets available to researchers worldside. Please see below for specific articles, papers, and datasets. We also make various IoT device signatures and destination lists available through the IoTrim Project. Our team has won one of the TOP 10 spots in the Telekom Challenge Development Stream. We have received a generous gift and an InnovateUK Cyber Security Academic Startup Accelerator Programme (CyberASAP) grant, supporting our efforts to accelerate IoT Security and to develop IoTrim. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2019 |
| Provided To Others? | Yes |
| Impact | Publications: Oliver Thompson, Anna Maria Mandalari, Hamed Haddadi, "Rapid IoT Device Identification at the Edge", 2nd Workshop on Distributed Machine Learning (DistributedML 2021), co-located with CoNEXT 2021, December 7-10, 2021, Munich, Germany. (Paper available on ArXiv) Anna Maria Mandalari, Daniel J. Dubois, Roman Kolcun, Muhammad Talha Paracha, Hamed Haddadi, David Choffnes, "Blocking without Breaking: Identification and Mitigation of Non-Essential IoT Traffic", in 21st Privacy Enhancing Technologies Symposium (PETS 2021), July 12-16, 2021, On the Internet. (Paper and code available on IoTrim) Said Jawad Saidi, Anna Maria Mandalari, Roman Kolcun, Hamed Haddadi, Daniel J. Dubois, David Choffnes, Georgios Smaragdakis, Anja Feldmann, "A Haystack Full of Needles: Scalable Detection of IoT Devices in the Wild", in ACM Internet Measurement Conference 2020, October 2020, Pittsburgh, Pennsylvania, USA. (Paper and data available) Daniel J. Dubois, Roman Kolcun, Anna Maria Mandalari, Muhammad Talha Paracha, David Choffnes, Hamed Haddadi, "When Speakers Are All Ears: Characterizing Misactivations of IoT Smart Speakers", in proceedings of the 20th Privacy Enhancing Technologies Symposium (PETS 2020), July 14-18, 2020, Montréal, Canada. (Paper, Webpage, Code, and Dataset, NYTimes, The Independent, and USA Today, BBC Panorama program Youtube Link, BBC News, Channel 4 The Truth About Amazon, NYT lead editorial, Vox, ZDNet, Telegraph, Gizmodo, GeekWire, Forbes, BusinessInsider) Anna Maria Mandalari, Roman Kolcun, Hamed Haddadi, Daniel J. Dubois, David Choffnes, "Towards Automatic Identification and Blocking of Non-Critical IoT Traffic Destinations", Workshop on Technology and Consumer Protection (ConPro '20), Co-located with the 41th IEEE Symposium on Security and Privacy, May 21, 2020, San Francisco, CA. (Paper available on ArXiv) Ranya Aloufi, Hamed Haddadi, David Boyle, "Emotionless: Privacy-Preserving Speech Analysis for Voice Assistants", in Privacy Preserving Machine Learning, ACM CCS 2019 Workshop, November 2019, London, UK. (Available on ArXiv, Articles on Vice, Medium) Jingjing Ren, Daniel J. Dubois, David Choffnes, Anna Maria Mandalari, Roman Kolcun, Hamed Haddadi, "Information Exposure From Consumer IoT Devices: A Multidimensional, Network-Informed Measurement Approach", in ACM Internet Measurement Conference 2019 (IMC 2019), October, 2019, Amsterdam, Netherlands. (Community Contribution Award) (paper and code and dataset, Financial Times article, The Times article, Vice article, BBC News, BBC Click program, Ars Technica) Media coverage: Consumer Reports: Connected Devices Share More Data Than Needed Channel 4 - The Truth About Amazon BBC News - Why Amazon knows so much about you BBC One (Panorama program) - Amazon: What They Know About Us (YouTube Link) BBC and BBC Click program on GDPR Anniversary (YouTube link) USA Today - It's not you, it's them: Google, Alexa and Siri may answer even if you haven't called The Independent - Smart Speakers Could Accidentally Record Users up to 19 Times Per Day, Study Reveals The New York Times - Are Alexa and Google Assistant spying on us? Which? - Are Alexa and Google Assistant spying on us? Centre for Data Ethics and Innovation first series of three snapshot papers on ethical issues in AI including Smart Speakers and Voice Assistants |
| URL | https://netsys.doc.ic.ac.uk/IoTLab.html |
| Description | BBC Research and Development |
| Organisation | British Broadcasting Corporation (BBC) |
| Department | BBC Research & Development |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | In 2018 we will showcase a live engagement event and demonstrator of the 'Future of the Living Room' with the BBC R&D at FACT in Liverpool as part of the States of play exhibition and at the Western Balkans Culture Summit. The living room will be open to the public at States of Play in May 2018 at FACT, Liverpooland at The Western Balkans Culture Summit in August 2018. We provided time, technical expertise, and Databox platform for the exhibition, as well as providing Hackathon and Exhibitions at the Mozilla Festival 2017. |
| Collaborator Contribution | The BBC are working on designing and creating an exhibition for a future immersive living room experience. This novel experience will explore the relationship between object based media (OBM) and Internet of Things (IoT) devices, taking advantage of the hyper-connected nature of our homes to provide new media experiences. Within this living room, we will demonstrate how a range of internet connected objects will adapt and personalise to people and to groups of people in several different ways within the shared space. We aim to show how we can create a personalised, immersive and engaging environment that is both entertaining and educational. This public engagement event and demonstrator is a piece of research that aims to demonstrate and evaluate the concept of IoT augmented experiences through broadcast media, as well as identify the implications of bi-directional, immersive and social broadcast media. There is the potential of this research helping to inform and establish a new framework for the future of media in a living room setting. When talking about the IoT there is a clear fear that personalised media (enabled by OBM) could potentially damage the social experience. When personalisation occurs in a shared space a range of research questions arise in light of how it will impact on the people sharing the space. For example, how will it impact on the social experience and how will it effect the issues around personal data, privacy and the exchange of data? This is a joint project between the BBC R&D, The British Council, the Databox team and the Foundation for Art and Creative Technology (FACT) Liverpool to create an exhibition for showcasing ideas for the living room. The live demonstrator will be open to the public and capture real-time IOT data and feedback to inform our understanding and to answer important research questions about personal data ethics, privacy and the social impact of the experience. |
| Impact | This partnership is part of an ongoing collaboration with the BBC R&D, which has already lead to engagement in joint activities in MozFest 2017 (https://www.databoxproject.uk/2017/09/02/databox-hackday-at-mozfest-2017-thu-26-oct/ ), MozFest 2016, in addition to the FACT in Liverpool. This |
| Start Year | 2017 |
| Description | BT Research and Development |
| Organisation | BT Group |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | We provided the Databox platform, demonstration, and IoT exemplar applications and devices in the BT Innovation showcase 2017. This exhibition is part of an ongoing collaboration between the Databox and BT R&D. |
| Collaborator Contribution | BT provided exhibition space for the Databox team at the BT Innovation week at Adastral Park. This was part of our ongoing collaboration with BT, leading to further research in the IoT space in 2018-2019. |
| Impact | our team showcased our Databox platform at BT Innovation week at Adastral Park, Ipswich, UK. There were nearly 5000 visitors over 5 days at the show. Over the week, our team talked to a mix of businesses - a couple of banks, healthcare providers, a housing association, IoT developers, BBC, Sky, EPSRC and BT researchers. We presented three use-cases: fraud detection, personalised adverts and health insurance. Many attendees were able to see use-cases for their sectors - typical questions were "how much will it cost?", "when will it be ready/commercialised?", "how centralised local datastore model is more secure than distributed", "what would be the physical form factor of the product if deployed?", "Does it require dedicated hardware?", "Can it run in BT's home hub", "how data usage would be analysed". In addition to this, many industry attendees mentioned concerns around GDPR (EU - General Data Protection Regulation) and could see how Databox can help industries/businesses to address the personal data storage related issues. Most of the discussions were about the overall concept and were around "how would I do this/that" and discussion on new potential applications. Overall, the project got positive feedback and follow-up invitations from the audience. |
| Start Year | 2017 |
| Description | Telefonica Research |
| Organisation | Telefonica S.A |
| Department | Telefonica Research |
| Country | Spain |
| Sector | Private |
| PI Contribution | Research on edge computing and privacy-preserving analytics |
| Collaborator Contribution | internships to PhD students, industry expertise provided for opensource projects |
| Impact | Fan Mo, Hamed Haddadi, Kleomenis Katevas, Eduard Marin, Diego Perino, Nicolas Kourtellis, "PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments", in The 19th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys 2021), Online, July 2021. ( Best Paper Award at MobiSys 2021) |
| Start Year | 2017 |
| Title | The Databox Platform |
| Description | The open source platform and app ecosystem code is on our developing repository on GitHub. The Databox platform is an open-source personal networked device, augmented by cloud-hosted services, that collates, curates, and mediates access to an individual's personal data by verified and audited third-party applications and services. The Databox will form the heart of an individual's personal data processing ecosystem, providing a platform for managing secure access to data and enabling authorised third parties to provide the owner with authenticated services, including services that may be accessed while roaming outside the home environment. |
| Type Of Technology | Software |
| Year Produced | 2017 |
| Impact | There have been numerous individuals and organisations which have used the Databox platform as part of their ongoing research. These include ISPs (KDDI in Japan), media industry (BBC R&D) and enthusiasts. The Databox papers and platform have been already highly cited in ~100 papers. |
| Title | The databox IoT software development kit |
| Description | The databox editor is a reimplementation of the node-red frontend and is currently the main tool for building databox apps. It is a javascript application with the backend using nodejs/express/node-red and the frontend using React / Redux |
| Type Of Technology | Software |
| Year Produced | 2017 |
| Open Source License? | Yes |
| Impact | This software is still in development but has been used at several events to demonstrate the databox concept and is currently being studied for research publication. |
| URL | https://github.com/me-box/platform-sdk |
| Description | BAE Systems Future Cities Horizon scanning conference |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Industry/Business |
| Results and Impact | Participated in the discussions and activities in the morning session (focus: Security, Privacy & Trust - presentations and workshop) and the afternoon session (focus: The Rise of Autonomy - presentations and workshop) |
| Year(s) Of Engagement Activity | 2017 |
| Description | BBC Salford symposium |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Media (as a channel to the public) |
| Results and Impact | Horizon and Databox presentation to BBC around privacy preserving personalised services |
| Year(s) Of Engagement Activity | 2018 |
| Description | BT Innovation Showcase, "Smart World", Adastral Park, June 2017 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | We provided and staffed a stand and demo of databox at the BT Innovation Showcase. An event to promote the best research and innovation in the communications industry, the future of customer experience, the importance of cyber security, and the evolution of organisation and machine learning. Project members engaged with hundreds of attendees over the 5-day events form BT senior executives, politicians and SMEs to industry practitioners. |
| Year(s) Of Engagement Activity | 2017 |
| URL | http://connect2.globalservices.bt.com/innovationweek2017 |
| Description | Creating the living room of the future |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Public/other audiences |
| Results and Impact | In 2018 we will showcase a live engagement event and demonstrator of the 'Future of the Living Room' with the BBC R&D at FACT in Liverpool as part of the States of play exhibition and at the Western Balkans Culture Summit. The living room will be open to the public at States of Play in May 2018 at FACT, Liverpooland at The Western Balkans Culture Summit in August 2018. |
| Year(s) Of Engagement Activity | 2018 |
| URL | http://www.bbc.co.uk/rd/blog/2017-10-on-the-living-room-of-the-future |
| Description | Data Harvesting Problem - Computerphile YouTube Video |
| Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | The educational video on Databox Privacy , part of University of Nottingham's Computerphile series: How do we control our own data while allowing it to be mined? Dr Richard Mortier of The University of Cambridge discusses some of the issues behind data harvesting. |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://www.youtube.com/watch?v=2lEhamPHh3k |
| Description | Databox Annual Symposium: Fri, November 17, 2017 |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Study participants or study members |
| Results and Impact | The Databox project held its first birthday this November. A lot has happened since last year, especially on the platform and analytics side. In the Year 1 roundup of the research, we presented papers, prototype, and demos of the Databox project. The event was held at the IET London and included fun and interactive demos with personal data and IoT devices, in addition to research highlights, panel discussions, and debates around the next steps for the project over the next 2 years. Invited Speakers: Joel Obstfeld (Distinguished Engineer , Cisco) Eleanor Birrell (PhD candidate, Cornell University) Andrius Aucinas (Head of Engineering at the Hub of All Things project) Laura James (Technology Principal at Doteveryone) Guy Cohen (Strategic Relationships Manager, Privitar) |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://www.eventbrite.com/e/databox-annual-symposium-tickets-37562808371 |
| Description | Databox Hack Day at the 2017 Mozilla Festival |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | A hack day held at the pioneering Internet privacy event 'Mozfest', introducing developers and the public at large to the Databox infrastructure |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://guidebook.com/guide/114124/event/16836420/ |
| Description | Databox HackDay at MozFest 2017 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | We will present the public release of a working open source Databox platform, which can be run on any device capable of running Docker containers. We endeavour to provide support for ARM devices such as the Raspberry Pi 3 for this release. This initial release has basic data collection support through mobile sensing libraries and selected APIs, provides basic data flow policing and privacy policy enforcement, and supports installation and operation of simple personal data processing apps. At this event we will briefly introduce and demo the Databox to you, then we hope to engage with security & privacy enthusiasts, data visualisation & analytics fans, and potential app developers to begin building a community and ecosystem around the Databox. We're open to contributions of all kinds, from improvements to core components, to helping you integrate your favourite IoT devices, to brainstorming what apps and devices you want to see the Databox support! |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://www.databoxproject.uk/2017/09/02/databox-hackday-at-mozfest-2017-thu-26-oct/ |
| Description | Databox Twitter account |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | Databox Twitter account to engage with the public and industry! |
| Year(s) Of Engagement Activity | 2017,2018 |
| URL | https://twitter.com/DataboxProject |
| Description | Databox poster and presentation at The 2nd workshop on Personal Data Systems, Sommarøy, Norway (PDS 2017) |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | Databox talk and poster at The 2nd workshop on Personal Data Systems, Sommarøy, Norway (PDS 2017) Hosted by the Department of Computer Science, UiT - The Arctic University of Norway, Schedule and slides available on: http://www.corporesano.no/eventspersonal-data-systems-workshop-2017pds-2017-program-preliminary/ |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://haddadi.github.io/PDS2017/ |
| Description | Databox posters at EuroSys 2017 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | There there 3 PhD student posters on display during the Security and Privacy session at the 11th EuroSys Doctoral Workshop 2017, in Belgrade: Route-based authorization and discovery for personal data by Yousef Amar (Queen Mary University of London) Towards Security in Distributed Home System by Jianxin Zhao (University of Cambridge) Towards Privacy-Preserving IoT Data Publishing by Mohammad Malekzadeh (Queen Mary University of London) |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://eurodw17.kaust.edu.sa/ |
| Description | Databox talk at the University of Washington Allen School Microsoft Research Summer Institute |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Databox talk to industry and academia audience at the UW Allen School MSR Summer Institute 2017 on Unpacking the Future of IoT |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://haddadi.github.io/UWMSRsummerInstDay1/ |
| Description | Databox: Hack and App, Mozilla Festival, October 2016 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | We introduce the Databox platform to the Mozilla community and provide participants with the opportunity to get their hands on this novel privacy-preserving platform. This hands on session will exploit data provided by Internet of Things devices deployed around the Mozilla Festival. Participants will be provided with a brief overview of the Databox platform before being invited to build 'apps' that sit on the Databox. Exploiting a modified Node Red app-building environment, participants will discover how to make apps that respect the requirement of informed consent and allow individuals to exercise granular choice over data processing; choices which are translated into enforceable policies on the Databox and govern data access and use. |
| Year(s) Of Engagement Activity | 2016 |
| URL | https://app.mozillafestival.org/#_session-172 |
| Description | Japan IoT workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | Organised and led with Japanese colleague workshop around IoT involving academics and industry in discussions around appropriate uptake in respective societies; continued search for joint funding to take this collaboration forward. |
| Year(s) Of Engagement Activity | 2017 |
| Description | Mindtech 2017 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Presentation on how Databox can alleviate ethical and privacy challenges in mental health care. |
| Year(s) Of Engagement Activity | 2017 |
| URL | http://www.mindtech.org.uk/mindtech-annual-conference.html |
| Description | Mozfest 2016 - Databox: Hack an App |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | The Databox - www.databoxproject.uk - provides a radical alternative to widespread data harvesting and data processing 'in the cloud'. Instead data processing takes place 'on the box' and is limited to what is needed to deliver specific services. We introduce the Databox platform to the Mozilla community and provide participants with the opportunity to get their hands on this novel privacy-preserving platform. This hands on session will exploit data provided by Internet of Things devices deployed around the Mozilla Festival. Participants will be provided with a brief overview of the Databox platform before being invited to build 'apps' that sit on the Databox. Exploiting a modified Node Red app-building environment, participants will discover how to make apps that respect the requirement of informed consent and allow individuals to exercise granular choice over data processing; choices which are translated into enforceable policies on the Databox and govern data access and use. |
| Year(s) Of Engagement Activity | 2016 |
| URL | https://app.mozillafestival.org/#_session-172 |
| Description | Mozfest 2016 - Databox: Hack an App (Hack On 1) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | This is a quiet hack following the previous hack a Databox session - www.databoxproject.uk - Introducing the Databox platform to the Mozilla community and provide participants with the opportunity to get their hands on this novel privacy-preserving platform. This hands on session will exploit data provided by Internet of Things devices deployed around the Mozilla Festival. |
| Year(s) Of Engagement Activity | 2016 |
| URL | https://app.mozillafestival.org/#_session-1172 |
| Description | Mozfest 2016 - Databox: Hack an App (Hack On 2) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | This is a quiet hack following the previous hack a Databox session - www.databoxproject.uk - Introducing the Databox platform to the Mozilla community and provide participants with the opportunity to get their hands on this novel privacy-preserving platform. This hands on session will exploit data provided by Internet of Things devices deployed around the Mozilla Festival. |
| Year(s) Of Engagement Activity | 2016 |
| URL | https://app.mozillafestival.org/#_session-1173 |
| Description | Mozfest 2016 - Introducing the Databox |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | The Databox - www.databoxproject.uk - provides a radical alternative to widespread data harvesting and data processing 'in the cloud'. Instead data processing takes place 'on the box' and is limited to what is needed to deliver specific services. We introduce the Databox platform to the Mozilla community and provide participants with the opportunity to get their hands on this novel privacy-preserving platform. |
| Year(s) Of Engagement Activity | 2016 |
| URL | https://app.mozillafestival.org/#_session-950 |
| Description | Rolls Royce workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | Invited to brainstorming session of future use of "Databox-like" architectures in future autonomous ships. |
| Year(s) Of Engagement Activity | 2017 |
| Description | Royal Academy of Engineering report on Data Sharing |
| Form Of Engagement Activity | A magazine, newsletter or online publication |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Policymakers/politicians |
| Results and Impact | Databox has been featured as a case study at the Royal Academy of Engineering report "Towards trusted data sharing: guidance and case studies" Read all about it here: http://reports.raeng.org.uk/datasharing/cover/ |
| Year(s) Of Engagement Activity | 2019 |
| URL | http://reports.raeng.org.uk/datasharing/cover/ |
| Description | Science Fair, Mozilla Festival, October 2016 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | We introduce the Databox platform to the Mozilla community. Approximately 200 attendees were engaged with at the science fair poster and demos session. |
| Year(s) Of Engagement Activity | 2016 |
| URL | https://app.mozillafestival.org/#_session-950 |
| Description | The Databox Open-Source Software Community Launch |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Postgraduate students |
| Results and Impact | The team working on the Databox Project hosted their Cambridge open-source community launch on Friday 24th March at Darwin College, Cambridge. The event served to introduce the motives behind Databox, the structure of the project and to gauge use cases within the community and potential application developers. The team presented the initial release of a working open source Databox platform, which includes basic data collection support through mobile sensing libraries and selected APIs, provides basic data flow policing and privacy policy enforcement, and supports installation and operation of simple personal data processing apps. The morning session began with a formal introduction by Hamed Haddadi into the research project itself, explaining the high-level goals of the project: "Can we do detailed, user-centric, contextual analytics at a scalable rate without privacy disasters and legal challenges?" Richard Mortier followed with a summary of the technical architecture of the Databox and described the driving motive as an open-source, personal networked system, NOT another data silo that acts as a honey pot - the focus being to move computation to where the data is, thus reducing the movement of data itself. Tosh Brown and Yousef Amar then followed with (working!) demonstrations of the Databox SDK and UI, and development of drivers and applications at the container level. The afternoon session was driven by the attendees, who were all asked to propose applications for and uses of the Databox, with small focus groups facilitating this development. |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://www.databoxproject.uk/2017/03/28/databox-open-source-software-community-launch-2/ |
| Description | The Kitchen Demo Databox in collaboration with BBC R&D, Mozilla Festival, October 2016 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | In collaboration with BBC R&D, Nottingham, Cambridge and Queen Mary universities present the Databox - www.databoxproject.uk - to drive community engagement with and discussion of the dilemmas of connected spaces. The Databox allows people to control access to personal data generated by Internet-enabled things, and allows them to exploit that data for their own benefit. Lucky participations will take part in making a cold chocolate dessert in front of a live audience, following a novel 'object-based media' recipe that exploits data from their interactions with Internet-enabled appliances, utensils and food packaging to deliver timely and appropriate video instructions. Getting your hands on our connected future will drive discussion of the positives and negatives of using the personal data produced in our mundane interactions with everyday things to drive new media experiences. Of course, participants will also be able to eat and enjoy the fruits of their labour. Bon appétit! |
| Year(s) Of Engagement Activity | 2016 |
| URL | https://app.mozillafestival.org/#_session-171 |
| Description | Victoria and Albert Museum exhibition of the Living room of the future |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | Full details via https://www.bbc.co.uk/rd/projects/databox and https://www.eventbrite.co.uk/e/the-living-room-of-the-future-at-the-va-museum-tickets-48129449479# The Living Room of the Future BBC R&D and the Databox team are also, in collaboration with the Foundation for Art and Creative Technology (FACT) and the British Council, organising a public experiment called 'The Living Room of the Future', which seeks to explore the relationship between our hyper-connected homes and next generation broadcasting techniques in ways that enhance inhabitants' media experiences while protecting their privacy and security. The HDI principles that underpin Databox development have also been applied in an innovative collaboration with BBC R&D centring on 'Object Based Media' (OBM). OBM adapts media to devices, environments, and people to create bespoke personalised experiences. BBC R&D and the Databox team undertook a public experiment at the 2016 Mozilla Festival to explore the potential relationship between OBM and Databox. The experiment leveraged the OBM 'Cook-Along Kitchen Experience' alongside Internet of Things technologies to engage members of the public in an innovative cooking experience. Mediated by the Databox, the experience used data generated by participants' interactions with Internet-enabled utensils and kitchen appliances to drive the timely delivery of recipe instructions. |
| Year(s) Of Engagement Activity | 2018 |
| URL | https://www.bbc.co.uk/rd/projects/databox |
| Description | https://www.eventbrite.com/e/databox-annual-symposium-tickets-37562808371 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Public/other audiences |
| Results and Impact | As part of the Mozilla Festival 2017, we held the Databox Hackathon event as a joint summit hosted under the Mozilla Festival pre-week events and a BBC R&D community event. We presented the public release of a working open source Databox platform, which can be run on any device capable of running Docker containers. This initial release had basic data collection support through mobile sensing libraries and selected APIs, provides basic data flow policing and privacy policy enforcement, and supports installation and operation of simple personal data processing apps. At this event we briefly introduced and demod the Databox, then we engaged with security & privacy enthusiasts, data visualisation & analytics fans, and potential app developers to begin building a community and ecosystem around the Databox. |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://www.eventbrite.com/e/databox-hackday-at-mozfest-2017-tickets-37382940381 |