[perpass] Infer 2016 - Int. Workshop on Inference and Privacy. Deadline approaching

"Simo Fhom, Hervais-Clemence" <hervais.simo@sit.fraunhofer.de> Sun, 17 April 2016 11:23 UTC

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From: "Simo Fhom, Hervais-Clemence" <hervais.simo@sit.fraunhofer.de>
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Subject: [perpass] Infer 2016 - Int. Workshop on Inference and Privacy. Deadline approaching
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[Apologies to those who receive multiple copies of this Cfp/email]

Dear Colleagues,

Infer 2016 - the first International Workshop on Inference & Privacy in 
a Hyperconnected World [1] will be held in Darmstadt, Germany this year, 
as part of the Darmstadt Security & Privacy Week (SPW 2016).

The workshop aims to foster the interdisciplinary discussion on both 
theoretical and practical issues that applying inference techniques to 
either compromise or enhance data protection and privacy may entail. 
Infer2016 provides researchers and practitioners with a unique 
opportunity to share their perspectives on various aspects of privacy 
and inference.

Please consider submitting to Infer 2016! Submissions are due in less 
than one month, on May 13, 2016.

Best regards,

Hervais Simo

[1] https://www.sit.fraunhofer.de/en/infer2016/


*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 hyper-connected 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 tools. 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

·Anonymous communication

·Discrimination-aware Learning

·Privacy-preserving deep learning models

·Deep learning models for privacy

·Privacy-preserving clustering, ranking, regression, etc.

·Privacy and anonymity metrics

·Statistical disclosure control

·Differential privacy and relaxations

·Machine learning and statistical inference on encrypted data

·Machine learning and statistical inference for cybersecurity (e.g., for 
malware and misbehaviour detection, analysis, prevention)

·Social graph matching and de-anonymization techniques

·Private information retrieval

·Algorithms and accountability

·Case studies and experimental datasets

·Legal, regulatory, and ethical issues



*Important Dates*


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

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 

·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 20 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 

It is planned to publish revised selected papers as a post-proceedings 
volume in Springer Verlag’s LNCS series (final approval pending).**


*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*


Rafael Accorsi, PWC, Switzerland

Nikita Borisov, University of Illinois at Urbana-Champaign, USA

Ulf Brefeld, Leuphana University Lüneburg, Germany

Michael Brückner, Amazon, Germany

Yves-Alexandre de Montjoye, MIT, USA

Shlomi Dolev, Ben-Gurion University, Israel

Tariq Elahi, KU Leuven, Belgium

Simone Fischer-Hübner, Karlstad University, Sweden

Marit Hansen, ULD, Germany

Stratis Ioannidis, Northeastern University, USA

Aaron D. Jaggard, U.S. Naval Research Laboratory, USA

Frederik Janssen, Technische Universität Darmstadt, Germany

Anja Lehmann, IBM Research Zürich, Switzerland

Daniel Le Métayer, INRIA, France

Tobias Matzner, University of Tübingen, Germany

Helen Nissenbaum, New York University, USA

Stefan Schiffner, ENISA, Greece

Haya Shulman, Fraunhofer SIT, Germany


*Publicity Co-chairs*


Fatemeh Shirazi, KU Leuven, Belgium

Christian Zimmermann, University of Freiburg, Germany