[TYPES/announce] Theory and Practice of Differential Privacy (TPDP) 2018 Call for Papers

[Gaboardi, Marco]

Theory and Practice of Differential Privacy (TPDP) 2018 Call for Papers
Colocated with CCS 2018 - October 15 - Toronto, Canada

Differential privacy is a promising approach to privacy-preserving data analysis. Differential privacy provides strong worst-case guarantees about the harm that a user could suffer from participating in a differentially private data analysis, but is also flexible enough to allow for a wide variety of data analyses to be performed with a high degree of utility. Having already been the subject of a decade of intense scientific study, it has also now been deployed in products at government agencies such as the U.S. Census Bureau and companies like Apple and Google.

Researchers in differential privacy span many distinct research communities, including algorithms, computer security, cryptography, databases, data mining, machine learning, statistics, programming languages, social sciences, and law. This workshop will bring researchers from these communities together to discuss recent developments in both the theory and practice of differential privacy.

Specific topics of interest for the workshop include (but are not limited to): – theory of differential privacy,
– privacy preserving machine learning,
– differential privacy and statistics,
– differential privacy and security,
– differential privacy and data analysis,
– trade-offs between privacy protection and analytic utility, 
– differential privacy and surveys,
– programming languages for differential privacy,
– relaxations of the differential privacy definition,
– differential privacy vs other privacy notions and methods, 
– experimental studies using differential privacy,
– differential privacy implementations,
– differential privacy and policy making,
– applications of differential privacy.

Submissions: The goal of TPDP is to stimulate the discussion on the relevance of differentially private data analyses in practice. For this reason, we seek contributions from different research areas of computer science and statistics. Authors are invited to submit a short abstract (2-4 pages maximum) of their work. Submissions will undergo a lightweight review process and will be judged on originality, relevance, interest and clarity. Submission should describe novel works or works that have already appeared elsewhere but that can stimulate the discussion between different communities at the workshop. Accepted abstracts will be presented at the workshop either as a talk or a poster.

The workshop will not have formal proceedings and is not intended to preclude later publication at another venue. Please format your submissions according to the instructions in https://www. sigsac.org/ccs/CCS2018/papers/. Submissions will be accepted at https://easychair.org/ conferences/?conf=tpdp18.

Important dates:

– Abstract submission: July 20 (anywhere on Earth), 
– Author Notification: August 13,
– Workshop: October 15.

Website: http://tpdp.cse.buffalo.edu/2018/

Program committee:

• Aleksandar Nikolov (chair), University of Toronto 
• Raef Bassily, Ohio State University
• Mark Bun, Boston University
• Michael Hay, Colgate University
• Vishesh Karwa, Temple University 
• Katrina Ligett, Hebrew University 
• Anand Sarwate, Rutgers University 
• Thomas Steinke, IBM
• Reza Shokri, National University of Singapore 
• Kunal Talwar, Google