Secure Multi-Party Computation

Secure Multi-Party Computation
Name	Secure Multi-Party Computation
Inventors	Oded Goldreich, Shafi Goldwasser, Silvio Micali
Year	1982
Related to	Cryptography, Distributed computing

Secure Multi-Party Computation is a subfield of Cryptography that enables multiple parties to jointly perform computations on their private data without revealing their individual inputs to each other, as demonstrated by Andrew Yao and Oded Goldreich. This concept has been extensively explored by researchers such as Shafi Goldwasser, Silvio Micali, and Tal Rabin, who have made significant contributions to the field. The work of Michael Rabin and Richard Karp has also been influential in the development of secure multi-party computation protocols. Additionally, the research of Noam Nisan and Amir Herzberg has shed light on the applications of secure multi-party computation in various fields, including Computer science and Artificial intelligence.

Introduction to Secure Multi-Party Computation

Secure multi-party computation has its roots in the work of Andrew Yao, who introduced the concept of secure two-party computation in the 1980s, building on the foundations laid by Claude Shannon and Alan Turing. The idea was later extended to multi-party computation by Oded Goldreich, Shafi Goldwasser, and Silvio Micali, who developed the first secure multi-party computation protocols, leveraging the work of Leonard Adleman and Ronald Rivest. These protocols have been widely used in various applications, including Electronic voting systems, Auction theory, and Data mining, as demonstrated by researchers such as Cynthia Dwork and Moni Naor. The development of secure multi-party computation has also been influenced by the work of Donald Knuth and Robert Tarjan, who have made significant contributions to the field of Computer science.

Principles and Definitions

The principles of secure multi-party computation are based on the concept of Secure function evaluation, which was introduced by Oded Goldreich and Benny Chor. This concept enables multiple parties to jointly compute a function on their private inputs without revealing their individual inputs to each other, as demonstrated by Yehuda Lindell and Benny Pinkas. The definition of secure multi-party computation involves the notion of Semantic security, which was introduced by Goldwasser and Micali, and has been widely used in various cryptographic protocols, including Public-key cryptography and Homomorphic encryption, as developed by Ronen Shaltiel and Eyal Kushilevitz. The work of Jonathan Katz and Yehuda Lindell has also been influential in the development of secure multi-party computation protocols, particularly in the context of Distributed computing and Cloud computing.

Protocols and Techniques

Various protocols and techniques have been developed for secure multi-party computation, including Yao's garbled circuit protocol, which was introduced by Andrew Yao, and Goldreich-Micali-Wigderson protocol, which was developed by Oded Goldreich, Shafi Goldwasser, and Avi Wigderson. These protocols have been widely used in various applications, including Secure multi-party sorting, Secure multi-party set intersection, and Secure multi-party matrix multiplication, as demonstrated by researchers such as Eyal Kushilevitz and Tal Rabin. The development of secure multi-party computation protocols has also been influenced by the work of Noam Nisan and Amir Herzberg, who have made significant contributions to the field of Game theory and Mechanism design, as applied to Auction theory and Electronic commerce.

Security Models and Threats

Secure multi-party computation protocols are designed to withstand various security threats, including Passive attacks, Active attacks, and Covert attacks, as defined by Matt Blaze and Martin Hellman. The security models used to analyze these protocols include the Semi-honest model, the Malicious model, and the Covert model, which were introduced by Oded Goldreich and Benny Chor. The work of Rafael Pass and Abhi Shelat has also been influential in the development of secure multi-party computation protocols, particularly in the context of Zero-knowledge proofs and Witness-indistinguishable proofs, as developed by Silvio Micali and Shafi Goldwasser.

Applications and Use Cases

Secure multi-party computation has various applications and use cases, including Secure electronic voting systems, Secure auctions, and Secure data mining, as demonstrated by researchers such as Cynthia Dwork and Moni Naor. The development of secure multi-party computation has also been influenced by the work of Donald Knuth and Robert Tarjan, who have made significant contributions to the field of Computer science and Artificial intelligence. Additionally, the research of Jonathan Katz and Yehuda Lindell has shed light on the applications of secure multi-party computation in various fields, including Distributed computing and Cloud computing, as well as Cryptography and Information theory, as developed by Claude Shannon and Alan Turing.

Implementation and Efficiency Considerations

The implementation and efficiency of secure multi-party computation protocols are critical factors in their practical deployment, as demonstrated by researchers such as Eyal Kushilevitz and Tal Rabin. The development of efficient protocols has been influenced by the work of Noam Nisan and Amir Herzberg, who have made significant contributions to the field of Game theory and Mechanism design, as applied to Auction theory and Electronic commerce. The research of Rafael Pass and Abhi Shelat has also been influential in the development of secure multi-party computation protocols, particularly in the context of Zero-knowledge proofs and Witness-indistinguishable proofs, as developed by Silvio Micali and Shafi Goldwasser. Furthermore, the work of Oded Goldreich and Benny Chor has shed light on the implementation and efficiency considerations of secure multi-party computation protocols, including the use of Homomorphic encryption and Secure function evaluation, as demonstrated by Yehuda Lindell and Benny Pinkas.

Category:Cryptography