BDSP 2014 : First IEEE International Workshop on Big Data Security and Privacy

When     Oct 27, 2014 - Oct 30, 2014
Where     Washington DC, USA

Call For Papers
Big Data is characterized by the integration of a significant amount of
data, of varying modalities or types, at a pace that cannot be handled
by traditional data management systems. This has sparked innovation in
the collection, processing and storage of this data. The analytic
systems built to leverage Big Data have yielded (and hold even greater
promise to uncover) remarkable insights that enable a host of new
applications that were not thought possible prior to the era of Big Data.

However, with this capacity to contribute to and benefit the greater
good comes the responsibility to protect the subjects referenced in the
data sets. In this context, the old adage is correct - "With great
power, comes great responsibility". Ultimately, the data subjects own
the data and they stand to suffer most significantly from the data's

Thus, there needs to be advances in techniques for 1) ingesting Big Data
in a secure and privacy-preserving, 2) performing Big Data analysis in a
secure environment and in a privacy-preserving manner, and 3) storing
and enforcing retention policy securely (and in private modes) for Big
Data systems. If these solutions are not in place, then the willingness
of people to contribute their data to be included in a Big Data system
decreases. Additionally, Big Data professionals need to perform risk
analyses, as they relate to security and privacy, to get a realistic
view of the safety of the landscape.

There is a lot of work to be done in this emerging field. This workshop
is a venue for researchers and practitioners to come together and tackle
them in a supportive and stimulating environment.

This workshop will include (but is not limited to):

Security and/or Privacy Technologies for collecting, processing and
storing Big Data.
Theoretical Foundations of Security and/or Privacy of Big Data software,
protocols, systems and infrastructure.
Security and/or Privacy analysis of Big Data software, protocols,
systems and infrastructure.
Big Data Forensic Analysis.
Trust Management theory and software for Big Data.
Accountability Theory and Technologies for Big Data.
Integrating Legal considerations in Big Data Security and Privacy
solutions and technologies.
User studies on Security and Privacy for Big Data software, protocols,
systems and infrastructure.
Usable Security and Privacy for Big Data software, protocols, systems
and infrastructure.

Submission Deadline     Aug 30, 2014
Notification Due     Sep 20, 2014
Final Version Due     Oct 5, 2014

For more information, contact Tyrone Grandison
( or Raquel Hill (