| 書目名稱 | Privacy-Preserving Deep Learning |
| 副標(biāo)題 | A Comprehensive Surv |
| 編輯 | Kwangjo Kim,Harry Chandra Tanuwidjaja |
| 視頻video | http://file.papertrans.cn/757/756070/756070.mp4 |
| 概述 | Provides an overview of deep learning-based privacy-preserving.Discusses privacy issues in machine learning as a service.Addresses learning as one of the challenges in the context of privacy-preservin |
| 叢書名稱 | SpringerBriefs on Cyber Security Systems and Networks |
| 圖書封面 |  |
| 描述 | This book discusses the state-of-the-art in privacy-preserving deep learning (PPDL), especially? as a tool for machine learning as a service (MLaaS), which serves as an enabling technology by combining classical privacy-preserving and cryptographic protocols with deep learning. Google and Microsoft announced a major investment in PPDL in early 2019. This was followed by Google’s infamous announcement of “Private Join and Compute,” an open source PPDL tools based on secure multi-party computation (secure MPC) and homomorphic encryption (HE) in June of that year. One of the challenging issues concerning PPDL is selecting its practical applicability despite the gap between the theory and practice. In order to solve this problem, it has recently been proposed that in addition to classical privacy-preserving methods (HE, secure MPC, differential privacy, secure enclaves), new federated or split learning for PPDL should also be applied. This concept involves building a cloud framework that enables collaborative learning while keeping training data on client devices. This successfully preserves privacy and while allowing the framework to be implemented in the real world.?.?.This book prov |
| 出版日期 | Book 2021 |
| 關(guān)鍵詞 | Privacy-Preserving; Deep Learning; Machine Learning as a Service; Data Privacy; Privacy Issue on Deep Le |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-16-3764-3 |
| isbn_softcover | 978-981-16-3763-6 |
| isbn_ebook | 978-981-16-3764-3Series ISSN 2522-5561 Series E-ISSN 2522-557X |
| issn_series | 2522-5561 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
|Archiver|手機(jī)版|小黑屋|
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