Secure Multi-Party Computation Against Passive Adversaries (Paperback)

Ashish Choudhury

ISBN 10: 303112166X / ISBN 13: 9783031121661

Published by Springer International Publishing AG, Cham, 2023

About this Item

Paperback. This book focuses on multi-party computation (MPC) protocols in the passive corruption model (also known as the semi-honest or honest-but-curious model). The authors present seminal possibility and feasibility results in this model and includes formal security proofs. Even though the passive corruption model may seem very weak, achieving security against such a benign form of adversary turns out to be non-trivial and demands sophisticated and highly advanced techniques. MPC is a fundamental concept, both in cryptography as well as distributed computing. On a very high level, an MPC protocol allows a set of mutually-distrusting parties with their private inputs to jointly and securely perform any computation on their inputs. Examples of such computation include, but not limited to, privacy-preserving data mining; secure e-auction; private set-intersection; and privacy-preserving machine learning. MPC protocols emulate the role of an imaginary, centralized trusted third party (TTP) that collects the inputs of the parties, performs the desired computation, and publishes the result. Due to its powerful abstraction, the MPC problem has been widely studied over the last four decades. This book focuses on multi-party computation (MPC) protocols in the passive corruption model (also known as the semi-honest or honest-but-curious model). On a very high level, an MPC protocol allows a set of mutually-distrusting parties with their private inputs to jointly and securely perform any computation on their inputs. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9783031121661

Bibliographic Details

• Title: Secure Multi-Party Computation Against Passive Adversaries (Paperback)
• Publisher: Springer International Publishing AG, Cham
• Publication Date: 2023
• Language: English
• ISBN 10: 303112166X
• ISBN 13: 9783031121661
• Binding: Paperback
• Condition: new

About this title

Synopsis

This book focuses on multi-party computation (MPC) protocols in the passive corruption model (also known as the semi-honest or honest-but-curious model). The authors present seminal possibility and feasibility results in this model and includes formal security proofs. Even though the passive corruption model may seem very weak, achieving security against such a benign form of adversary turns out to be non-trivial and demands sophisticated and highly advanced techniques. MPC is a fundamental concept, both in cryptography as well as distributed computing. On a very high level, an MPC protocol allows a set of mutually-distrusting parties with their private inputs to jointly and securely perform any computation on their inputs. Examples of such computation include, but not limited to, privacy-preserving data mining; secure e-auction; private set-intersection; and privacy-preserving machine learning. MPC protocols emulate the role of an imaginary, centralized trusted third party (TTP) that collects the inputs of the parties, performs the desired computation, and publishes the result. Due to its powerful abstraction, the MPC problem has been widely studied over the last four decades.

About the Author

Ashish Choudhury, Ph.D., is an Associate Professor at the International Institute of Information Technology, Bangalore, India. He received his M.S. and Ph.D. degrees from the Indian Institute of Technology, Madras, India. His research interests include theoretical cryptography, with specialization in cryptographic protocols.

 

Arpita Patra, Ph.D., is an Associate Professor at the Indian Institute of Science. She received her Ph.D from the Indian Institute of Technology and held post-doctoral positions at the University of Bristol, ETH Zurich, and Aarhus University. Her research interests include cryptography, with a focus on theoretical and practical aspects of secure multiparty computation protocols.