Trusted Dynamic Coalitions was a one year research project in the
School of Computing Science in Newcastle University. We seek to
provide methods and tools that wil help coalition partners to choose
the right policies so that the desire for provenance data and the
desire for secrecy are held in balance. The project is due to start
on May 1st 2012.
A part-time Research Associate job is available on this project for 12 months. For further details, contact
Jeremy Bryans or
Paolo Missier.
In a virtual organisation, partners need to take action based on the
information they receive from other partners. This presents a problem,
because the information may not be trustworthy. To increase their
confidence that they are taking the right action, there are some
things a partner can do. They can ask the sender for more details
about the information itself, such as its source or age (known as the
provenance of the information), but these details can often give away
organisation or government secrets, and partners are naturally not
keen to release them. They could try to verify the information
themselves or via a third party, but these activities take time and
in situations such as disaster response, speed is an
important factor.
We wish to enable a partner to increase their confidence that they are
taking the right action in a virtual organisation. We will do this
by providing methods and tools that help partners to choose the
virtual organisation policies so that the desire for provenance data
and the desire for secrecy are held in balance.
We will look particularly at the provenance acquisition policy,
which states what provenance information is associated with
communications within the virtual organisation, and the provenance use
policy, which states the action that a partner will take on receipt of
information with a certain provenance associated to it.
Missier P, Bryans J, Gamble C, Curcin V, Danger R. Provenance graph abstraction by node grouping.
Submitted to Transactions on Knowledge and Data Engineering, available as School of Computing Science. Technical Report Number 1393 (download
PDF)
Curcin V., Danger R., Missier P. and Bryans J. Access control and views generation for OPM provenance graphs. (submitted to FGCS)
Missier P, Bryans J, Danger R, Curcin V. Preserving privacy in shared provenance data. School of Computing Science. 2013. School of Computing Science Technical Report Series Number 1366 (download
PDF)
ProvAbs: a tool for controlling the disclosure of sensitive provenance graphs. Paolo Missier, Carl Gamble, Jeremy Bryans (submitted EDBT)