SpringerBriefs on Cyber Security Systems and Networks - Privacy-Preserving Deep Learning Ebook Tooltip Ebooks kunnen worden gelezen op uw computer en op daarvoor geschikte e-readers. A Comprehensive Survey
Afbeeldingen
Sla de afbeeldingen overArtikel vergelijken
- Engels
- E-book
- 9789811637643
- 22 juli 2021
- Adobe ePub
Samenvatting
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 provides fundamental insights into privacy-preserving and deep learning, offering a comprehensive overview of the state-of-the-art in PPDL methods. It discusses practical issues, and leveraging federated or split-learning-based PPDL. Covering the fundamental theory of PPDL, the pros and cons of current PPDL methods, and addressing the gap between theory and practice in the most recent approaches, it is a valuable reference resource for a general audience, undergraduate and graduate students, as well as practitioners interested learning about PPDL from the scratch, and researchers wanting to explore PPDL for their applications.
Productspecificaties
Inhoud
- Taal
- en
- Bindwijze
- E-book
- Oorspronkelijke releasedatum
- 22 juli 2021
- Ebook Formaat
- Adobe ePub
Betrokkenen
- Hoofdauteur
- Kwangjo Kim
- Tweede Auteur
- Harry Chandra Tanuwidjaja
- Hoofduitgeverij
- Springer
Lees mogelijkheden
- Lees dit ebook op
- Desktop (Mac en Windows) | Kobo e-reader | Android (smartphone en tablet) | iOS (smartphone en tablet) | Windows (smartphone en tablet)
Overige kenmerken
- Studieboek
- Nee
EAN
- EAN
- 9789811637643
Je vindt dit artikel in
- Categorieën
- Boek, ebook of luisterboek?
- Ebook
- Taal
- Engels
- Beschikbaarheid
- Leverbaar
- Studieboek of algemeen
- Studieboeken
Kies gewenste uitvoering
Prijsinformatie en bestellen
De prijs van dit product is 69 euro.- E-book is direct beschikbaar na aankoop
- E-books lezen is voordelig
- Dag en nacht klantenservice
- Veilig betalen
Rapporteer dit artikel
Je wilt melding doen van illegale inhoud over dit artikel:
- Ik wil melding doen als klant
- Ik wil melding doen als autoriteit of trusted flagger
- Ik wil melding doen als partner
- Ik wil melding doen als merkhouder
Geen klant, autoriteit, trusted flagger, merkhouder of partner? Gebruik dan onderstaande link om melding te doen.