CALL FOR PAPERS
Workshop paper submission deadline: Monday, July 10, 2017 (11pm59 CET)
Workshop paper acceptance notification : Monday, July 24, 2017
Workshop date: Friday, September 22, 2017
We invite submissions of recent work on the combination of data mining (machine learning) and multi-party computation, theory as well as practice-oriented, like
- Data mining / machine learning implemented via garbled circuits or secret-sharing based MPC
- Classification and regression methods for use on secret-shared data
- Privacy-preserving delegation of data-mining-related computations to the cloud
- Private-data mining with verifiable results in the multi-party setting
- Federated learning
- Deep learning with secure learning and evaluation
- Performance evaluations of implementations of privacy-preserving data mining
- Data mining via multiparty computation in peer-to-peer scenarios (e.g. with mobile devices)
- Secure frequent pattern mining
- Sensor networks with multi-party secure data processing
- Privacy protecting commercial applications, like secure recommender systems and private set intersection
- Secure graph analytics
The workshop will not have formal proceedings, but authors of accepted abstracts can choose to have their work published on the workshop webpage. Submissions do not need to be anonymized.
We invite authors to submit extended abstracts (around 4 pages), position papers and regular technical papers (up to 12 pages including references and appendices).
We do accept submissions to this track that have recently been published, or are currently under submission elsewhere. We also encourage authors to submit (short) papers that describe work in progress. The Program Committee will select a subset of the papers for short presentations.
Note that at least one author of each accepted paper should be registered to the conference.
Papers must be written in English and formatted according to the Springer LNCS guidelines. Author instructions, style files and copyright form can be downloaded here.
Submissions can be sent via email to: n.j.bouman (at) tue.nl