Synthesis Lectures on Distributed Computing Theory Secure Multi Party Computation Against Passive Adversaries

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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. 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. In addition, this book: Includes detailed security proofs for seminal protocols and state-of-theart efficiency improvement techniques Presents protocols against computationally bounded as well as computationally unbounded adversaries Focuses on MPC protocols in the passive corruption model, presents seminal possibility and feasibility results, and features companion video lectures 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.

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Pages: 244, Edition: 1st ed. 2022, Paperback, Springer