This workshop focuses on privacy-preserving and robust data analysis in the distributed setting. With the emerging technologies (e.g. IoT, FoG/EDGE computing, and 5G), the traditional cloud computing model, which often aggregates data and performs centralized analysis, faces new challenges, including greater cost in aggregating the exponentially-growing distributed data and stricter privacy regulations. Recently, we see an increasing demand for distributed data analysis (e.g. training new models in machine learning), that on one hand empowers the data owners to protect their data and on the other hand creates new business models.
The main focus of this workshop is to investigate privacy-preserving and robust solutions for distributed data analysis, and to empirically study their performances with respect to well-known datasets. The data analysis tasks of interest include various machine learning and data mining algorithms, but not necessarily limit to them. Some example technology topics we are looking for include the following:
- Lightweight secure multi-party computation techniques
- (Partial) homomorphic encryption techniques
- Functional encryption schemes
- Differential privacy: theory and implementations
- Syntactic data disclosure notions (k-anonymity, l-diversity, t-closeness, etc.)
- Robustness attack detection in the distributed setting
- Adversarial examples in machine learning
- Trade-offs between different requirements (privacy, robustness, utility, etc.)
- Properties other than privacy and robustness: transparency, anti-discrimination, bias
- Exploration of distributed ledger technologies (DLTs) and Blockchain
- Adaptation of data analysis algorithms to facilitate protecting privacy and robustness
Aiming at networking people from different communities and bridging the gap between them, we naturally welcome other related topics and contributed talks to this workshop. In the long-term, we wish the workshop could foster fruitful collaborations to investigate rigorous and usable solutions for the practitioners.
- Workshop paper submission deadline: April 14, 2019
- Workshop paper notification: Apr 30, 2019
- Camera-ready papers for pre-proceedings: May 15, 2019
- Workshop dates: June 5-7, 2019 (in parallel with the main conference)
We accept two types of submissions. One type is original full papers, which should not be duplicated work that has published elsewhere or submitted to any other venue with formal proceedings. The submissions must be anonymous, with no author names, affiliations, acknowledgement or obvious references. Once accepted, the papers will appear in the formal proceedings. The submissions for this type must follow the original LNCS format (see http://www.springeronline.com/lncs) with a page limit of 18 pages (incl. references) for the main part (reviewers are not required to read beyond this limit) and 25 pages in total. Authors of accepted papers must guarantee that their paper will be presented at the conference and must make a full version of their paper available online. There will be a best paper award.
We also welcome the authors to submit poster papers, which can be ongoing work without the full analysis and experimental results. The submissions of this category is subject to the same format requirements, except with a page limit of 6 pages.
All papers will be published in LNCS, Springer.
Last but not the least, we welcome contributed talks to this workshop. In this case, please submit a title and abstract to the following email address.
Please submit your paper via the following link EasyChair System. If there is any question, please contact us at: email@example.com
Qiang Tang, Luxembourg Institute of Science and Technology, Luxembourg
Erman Ayday, Case western reserve university, USA and Bilkent University, Turkey
Gergely Biczok, Budapest University of Technology and Economics, Hungary
Xiaofeng Chen, Xidian University, China
Josep Domingo-Ferrer, Universitat Rovira i Virgili, Catalonia
Jinguang Han, University of Surrey, UK
Jiuyong LI, University of South Australia, Australia
Jianting Ning, NUS, Singapore
Melek Onen, EURECOM, France
Zhaohui Tang, SUTD, Singapore
Jun Wang, University of Luxembourg, Luxembourg
Jia Xu, Trustwave, Singapore
Yang Zheng, SUTD, Singapore
Jun Zhou, East China Normal University, China