PPMLP 2020: Workshop on Privacy-Preserving Machine Learning in Practice

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Abstract

With the rapid development of technology, data is becoming ubiquitous. User privacy and data security are drawing much attention over the recent years, especially with the European Union's General Data Protection Regulation (GDPR) and other laws coming into force. On one hand, from the customers' perspective, how to protect user privacy while making use of customers? data is a challenging task. On the other hand, data silos are becoming one of the most prominent issues for the society. From the business? perspective, how to bridge these isolated data islands to build better AI systems while meeting the data privacy and regulatory compliance requirements has imposed great challenges to the traditional machine learning paradigm. PPMLP will provide an opportunity to connect researchers from both CCS community and machine learning community to tackle these challenges.

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Zhang, B., Zaharia, M., Ji, S., Ada Popa, R., & Gu, G. (2020). PPMLP 2020: Workshop on Privacy-Preserving Machine Learning in Practice. In Proceedings of the ACM Conference on Computer and Communications Security (pp. 2139–2140). Association for Computing Machinery. https://doi.org/10.1145/3372297.3416245

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