Databox Version 0.5.0 released!

This version contains a rewritten core-arbiter, core-container-manger and a new set of build tools. There is now no javascript in the code of databox. Most of the core databox components now communicate over the ZestDB protocol, the language-specific libraries have been updated to reflect this change.

The databox user interface has been moved for the core-container-manger into its own component core-ui. This uses a new experimental store based API to access data and API endpoints within the container-manager. This enhances security and enables audit logging by default. It also has the benefit that new user interfaces can be developed in the same way as databox apps.

The platform-app server has also been removed in favour of a databox driver that read manifest from a git hub repository (driver-app-store).

With these changes, the core of databox is much more stable and should be easier or extend and develop on in the future.

Have fun, and as always expect bugs and dragons. Please report issues on the main me-box/databox repository.

The Databox Team


Research Associate/Senior Research Associate at the Cambridge University Computer Laboratory

Research Associate £31,604 – £38,833 or Senior Research Associate £39,992 – £50,618

Fixed-term: The funds for this post are available for 24 months.

A Research Associate post is available in the Systems Research Group at the Cambridge University Computer Laboratory for up to 2 years with the possibility of extension. Appointment to Senior Research Associate will be considered for exceptional candidates. We welcome applications from candidates with experience outside academia.

The Systems Research Group provides a supportive and rigorous environment in which to undertake world-leading research in a wide range of topics in computer systems. The group’s outputs are not limited to publications but often also include spin out companies significant successes include XenSource (acquired by Citrix Systems Inc. for $500M in 2007) and Unikernel Systems (acquired early last year by Docker Inc.).

The group holds a portfolio of projects supporting development, experimentation and data analysis in personal networked systems to support Human-Data Interaction including Databox and DADA .

This post will focus on design, development and systematic evaluation of technology prototypes for traffic management of domestic IoT devices. This will entail using technologies such as eBPF and Linuxkit to gather data to feed a range of machine learning algorithms, as well as consuming the results of those algorithms alongside user inputs to dynamically reconfigure network connectivity as device behaviours evolve.

Successful candidates will hold a Ph.D. in Computer Science, or have equivalent skills and experience through non-academic routes, and must be able to evidence:

  • Ability to communicate clearly in English, in both written and spoken forms.
  • Familiarity with the core Internet protocols (e.g., TCP/IP, UDP, DNS), the BSD Socket APIs, and Linux software development.
  • Experience of or aptitude for systems-level (e.g., OS kernel, device driver, assembly level) software development.
  • Experience of or aptitude for rigorous system measurement and evaluation, including experiment design, data capture, and data analysis. This may have been gained in commercial or industrial settings as well as through production of academic papers.

Other desirable characteristics include:

  • Evidence of an excellent publication record, commensurate with level of experience is also desirable. Candidates from outside academia may be able to evidence this by providing examples of rigorous technical writing published or distributed through channels other than academic conferences and journals.
  • Familiarity with machine learning algorithms, techniques and applications.

For more background information on the Systems Research Group, see where further information about the projects mentioned can also be found.

Informal enquiries should be directed to Richard Mortier (

To apply online for this vacancy, please click on the ‘Apply’ button below. This will route you to the University’s Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.

Please ensure you upload your Curriculum Vitae (CV) and a covering letter. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.

Please quote reference NR16300 on your application and in any correspondence about this vacancy.

The University values diversity and is committed to equality of opportunity.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

Research Associate Job at Imperial College London (Data Analytics/Privacy for personal/home data)

Applications are invited for a Senior Postdoctoral Research Associate position on Data mining, Analytics, Privacy Protocols and Machine Learning aspects of Personal and IoT data for the the EPSRC Databox Project ( ) and the EPSRC Defense Against Dark Artefacts project ( ), ideally with a focus on edge computing, Internet of Things, data mining, data visualization, or designing and implementation of and security and privacy protocols and machine learning algorithms.


Job listing information

  • Reference ENG00357
  • Closing date 1 July 2018

Salary £36,800 – £44,220 plus benefits

This is full time fixed term position for 14 months, with high possibility of further extensions.

Duties and responsibilities

  • Design and building efficient and scalable privacy protocols and machine learning algorithms in conjunction with the Databox system
  • Designing intuitive data discovery and visualisation apps for IoT/Personal data
  • Engage with the other team members in design and conduct of experiments assessing the interaction of users with exemplar apps and data
  • Work on a team including the PI, CoIs, and other PDRAs to design the Databox prototype

Further information and job details available via


Databox Version: 0.4.0

Databox Version 0.4.0 is now available for download:

Changes since last version:

Changes to me-box/databox:

  • Add funding/grant information see me-box/databox/pull/250
  • Always update node modules see me-box/databox/pull/247
  • enable broadcast traffic relay see me-box/databox/pull/243
  • Adds the needed authorization headers to the tests see me-box/databox/pull/241
  • Authentication see me-box/databox/pull/239
  • Update year in license see me-box/databox/pull/238

Changes to core repositories:

Changes to me-box/core-container-manager:

  • Fix app driver startup order see me-box/core-container-manager/pull/26
  • Fixes proxy DNS lookup errors see me-box/core-container-manager/pull/25
  • UI Updates see me-box/core-container-manager/pull/24
  • Adds a timeout and makes sure next() is called see me-box/core-container-manager/pull/23
  • Fix broken link #21 see me-box/core-container-manager/pull/22
  • Authentication see me-box/core-container-manager/pull/20

Changes to me-box/core-arbiter:

  • No changes in this version

Changes to me-box/core-export-service:

  • No changes in this version

Changes to me-box/core-network:

  • Enable driver to see broadcast packets see me-box/core-network/pull/5
  • ignore reverse lookup request see me-box/core-network/pull/4

Changes to me-box/core-store:

  • Update to zest 0.0.6 see me-box/core-store/pull/5
  • Update to v0.0.4 see me-box/core-store/pull/4
  • Move to jptmoore/zest:v0.0.4 see me-box/core-store/pull/3
  • Core-store v2 see me-box/core-store/pull/2

Changes to me-box/lib-node-databox:

  • Fix parsing of observe response with spaces in the payload see me-box/lib-node-databox/pull/36
  • Core store v2 see me-box/lib-node-databox/pull/35
  • Update to core-store v2 api see me-box/lib-node-databox/pull/34

Changes to me-box/lib-go-databox:

  • Fixes parseRawObserveResponse for payloads with spaces see me-box/lib-go-databox/pull/9
  • Update to new care-store API see me-box/lib-go-databox/pull/8

Market engagement in the Databox project

A new Report, commissioned by the Horizon Digital Research Institute, looks at the industry and consumer market engagement opportunities of the Databox project. The report looks at market engagement with the Databox concept, as it emerges from a limited number of conversations with project stakeholders, business consultants and industry experts. It seeks to explore its value proposition for individuals, ‘data-rich’ companies and ‘data-poor’ companies.

See the full report on



Creating the living room of the future…

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.

See the details on:

Databox Version: 0.2.0 released!

Databox Version 0.2 has been released in time for our MozFest 2017 Hackathon next week. See the release notes on:


Changes since last version:

Changes to me-box/databox:

Changes to core repositories:

Changes to me-box/core-container-manager:

Changes to me-box/core-arbiter:

Changes to me-box/core-export-service:

Changes to me-box/store-json:

Changes to me-box/store-timeseries:

  • No changes in this version

Changes to me-box/lib-node-databox:

Changes to me-box/lib-go-databox:

  • No changes in this version


Databox Annual Symposium: Fri, November 17, 2017

Please register via:

The Databox project will be have its first birthday this November. A lot has happened since last year, especially on the platform and analytics side. Please join us for the Year 1 roundup of the research, prototype, and demos of the Databox project. the event will be in the IET London and will include 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.

Confirmed Invited Speakers:

Joel Obstfeld (Distinguished Engineer , Cisco)

Eleanor Birrell (PhD candidate, Cornell University)

Andrius Aucinas (Head of Engineering at the Hub of All Thingsproject)

Laura James (Technology Principal at Doteveryone)

Guy Cohen (Strategic Relationships Manager, Privitar)


More information is on the Eventbrite page.

In the mean time, please keep in touch with us via the forum

Databox HackDay at MozFest 2017 (Thu. 26 Oct)

As part of Mozilla Festival 2017, we are inviting you to join us in Databox Hackathon event as a joint summit hosted under the Mozilla Festival pre-week events and a BBC R&D community event.

Please register here:

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!

The full schedule is available on the Eventbrite page.

Databox at BT Innovation 2017

Last week, 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.