Aravilli Privacy-Preserving Machine Learning

A use-case-driven approach to building and protecting ML pipelines from privacy and security threats
1. Auflage 2024
ISBN: 978-1-80056-422-0
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 402 Seiten

No detailed description available for "Privacy-Preserving Machine Learning".

Autoren/Hrsg.

Aravilli, Srinivasa Rao

Weitere Mitwirkende

Hamilton, Sam

Fachgebiete

• Technische Wissenschaften Technik Allgemein Technik: Allgemeines
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Datensicherheit, Datenschutz
• Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Naturwissenschaften, Technik, Medizin

Inhaltsverzeichnis

Table of Contents - Introduction to Data Privacy, Privacy threats and breaches
- Machine Learning Phases and privacy threats/attacks in each phase
- Overview of Privacy Preserving Data Analysis and Introduction to Differential Privacy
- Differential Privacy Algorithms, Pros and Cons
- Developing Applications with Different Privacy using open source frameworks
- Need for Federated Learning and implementing Federated Learning using open source frameworks
- Federated Learning benchmarks, startups and next opportunity
- Homomorphic Encryption and Secure Multiparty Computation
- Confidential computing - what, why and current state
- Privacy Preserving in Large Language Models

Über Autor(innen)

Aravilli Srinivasa Rao:
Srinivasa Rao Aravilli boasts 27 years of extensive experience in technology, research, and leadership roles, spearheading innovation in various domains such as Information Retrieval, Search, ML/AI, Distributed Computing, Network Analytics, Privacy, and Security. Currently working as a Senior Director of Machine Learning Engineering at Capital One, Bangalore, he has a proven track record of driving new products from conception to outstanding customer success. Prior to his tenure at Capital One, Srinivasa held prominent leadership positions at Visa, Cisco, and Hewlett Packard, where he led product groups focused on data privacy, machine learning, and Generative AI. He holds a Master's Degree in Computer Applications from Andhra University, Visakhapatnam, India.