--Apple-Mail=_7870E18E-889D-430C-8581-491070AB1789 Content-Type: multipart/alternative; boundary="Apple-Mail=_B67DD818-72CA-444B-A8CA-1C600FF40C8C" --Apple-Mail=_B67DD818-72CA-444B-A8CA-1C600FF40C8C Content-Transfer-Encoding: quoted-printable Content-Type: text/plain; charset=windows-1252 CALL FOR PAPERS ********************************************************************** Infer 2016: International Workshop on Inference and Privacy in a = Hyperconnected World July 18, 2016 Darmstadt, Germany https://www.sit.fraunhofer.de/en/infer2016/ ********************************************************************** 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=92 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 # =85 Important Dates ------------- Paper Submission deadline: June 1, 11:59pm PST, 2016 [extended] Notification: June 27, 2016 Camera ready: July 10, 2016 Workshop: July 18, 2016 Submission ------------- 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: =B7 # 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 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 = (https://www.easychair.org/conferences/?conf=3Dinfer2016). It is planned to publish revised selected papers as a post-proceedings = volume in Springer Verlag=92s 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 L=FCneburg, Germany Michael Br=FCckner, Amazon, Germany Yves-Alexandre de Montjoye, MIT, USA Shlomi Dolev, Ben-Gurion University, Israel Tariq Elahi, KU Leuven, Belgium Simone Fischer-H=FCbner, Karlstad University, Sweden Marit Hansen, ULD, Germany Stratis Ioannidis, Northeastern University, USA Aaron D. Jaggard, U.S. Naval Research Laboratory, USA Frederik Janssen, Technische Universit=E4t Darmstadt, Germany Anja Lehmann, IBM Research Z=FCrich, Switzerland Daniel Le M=E9tayer, INRIA, France Tobias Matzner, University of T=FCbingen, 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 --Apple-Mail=_B67DD818-72CA-444B-A8CA-1C600FF40C8C Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset=windows-1252

CALL FOR = PAPERS

July 18, 2016 Darmstadt, Germany

https://www.sit.fraun= hofer.de/en/infer2016/
= **********************************************************************

=

-------------

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=92 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):

#    = Discrimination-aware Learning 
#     Privacy-preserving deep = learning models 
#    =85 

-------------

Paper Submission = deadline: June 1, 11:59pm PST, 2016 [extended]

Notification: June = 27, 2016

Camera ready: July 10, 2016

Workshop: July 18, = 2016

 

Submission

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:

=B7         = #    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 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 (https://w= ww.easychair.org/conferences/?conf=3Dinfer2016).


Program Committee = Chairs

-------------

Michael Waidner, = Fraunhofer SIT / TU Darmstadt, Germany

Thorsten Strufe, TU = Dresden, Germany

Amir Herzberg, Bar Ilan University, Israel

 

Program = Committees

-------------

Rafael Accorsi, PWC, = Switzerland

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

Ulf Brefeld, Leuphana University L=FCneburg, = Germany

Michael Br=FCckner, Amazon, Germany

Shlomi Dolev, Ben-Gurion = University, Israel

Tariq Elahi, KU Leuven, Belgium

Stratis Ioannidis, Northeastern = University, USA

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

Frederik Janssen, Technische Universit=E4t Darmstadt, = Germany

Anja Lehmann, IBM Research Z=FCrich, = Switzerland

Daniel Le M=E9tayer, INRIA, France

Helen Nissenbaum, = New York University, USA

Stefan Schiffner, ENISA, Greece

 

-------------

Christian Zimmermann, = University of Freiburg, Germany


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