Infer 2016: International Workshop on Inference and Privacy in a
Hyperconnected World

July 18, 2016 Darmstadt, Germany


Motivation and Scope

The fields of embedded computing, wireless communication, data mining
and artificial intelligence are exhibiting impressive
improvements. Their combination fosters the emergence of "smart
environments": Systems made of networked physical objects embedded in
public places and private spheres of everyday individuals. This trend
is supporting the rise of a broad variety of data-driven services that
are highly customized to various aspect of our life, and hold great
social and economic potential. Examples include wearable computing
systems and applications for monitoring of personal health and
physical/social activities; Intelligent Transport Systems (ITS)
relying on cars that are becoming increasingly aware of their
environment and drivers; and home automation systems that even support
face and emotion recognition applications and provide web access to
entirely novel types of content.

Such disruptive technologies are expected to increasingly rely on
sophisticated machine learning and statistical inference techniques to
obtain a much clearer semantic understanding of people' states,
activities, environments, contexts and goals. However, these
developments also raise new technical, social, ethical and legal
privacy challenges which, if left unaddressed, will jeopardize the
wider deployment and thus undermine potential social and economic
benefits of the aforementioned emerging technologies. Indeed,
algorithms increasingly used for complex information processing in
today's hyperconnected society are rarely designed with privacy and
data protection in mind. On the other hand, privacy researchers are
increasingly interested in leveraging machine learning and inference
models when designing both attacks and innovative privacy-enhancing

Aiming to foster an exchange of ideas and an interdisciplinary
discussion on both theoretical and practical issues that applying
inference models to jeopardize/enhance data protection and privacy may
entail, this workshop provides researchers and practitioners with a
unique opportunity to share their perspectives with others interested
in the various aspects of privacy and inference. Topics of interest
include (but are not limited to):

Adversarial learning and emerging privacy threats
Privacy and anonymity metrics
Deep learning privacy Anonymous communication
Social graph matching and de-anonymization techniques
Private information retrieval
Statistical disclosure control
Privacy preserving regression, clustering, regression, ranking, etc.
Discrimination-aware Learning
Machine learning and statistical inference on encrypted data
Machine learning and statistical inference for cybersecurity (e.g., for malware and misbehaviour detection, analysis, prevention)
Algorithms and accountability
Case studies and experimental datasets
Legal, regulatory, and ethical issues

Important Dates

Paper Submission deadline: May 13, 2016 11:59pm PST

Notification: June 20, 2016

Camera ready: July 10, 2016

Workshop: July 18, 2016


The workshop seeks to bring together experts and practitioners from
academia, industry and government to discuss open research problems,
case studies, and legal and policy issues related to inference and
privacy. Authors are invited to submit either:

Full research papers that present relatively mature research results
on topics related to data analysis /statistical inference and
privacy/data protection;

Short papers that discuss new attacks and inspiring visions for
countermeasures, or present interdisciplinary research related to case
studies and legal and policy issues; or

Industry papers that share practical experiences.

Papers must be written in English. Authors are required to follow LNCS
guidelines. The length of the full paper (in the proceedings format)
must not exceed 16 pages, including the bibliography and well-marked
appendices. Short papers and industry papers must not exceed 9
pages. PC members are not required to read the appendices, and so the
paper should be intelligible without them.

Papers are to be submitted electronically and in pdf format only using
the EasyChair conference management system

INFER 2016 will publish formal proceedings of the accepted papers in
Springer Verlag's LNCS series.

Program Committee Chairs

Michael Waidner, Fraunhofer SIT / TU Darmstadt, Germany
Thorsten Strufe, TU Dresden, Germany
Amir Herzberg, Bar Ilan University, Israel
Hervais Simo, Fraunhofer SIT, Germany

Program Committees

Please see