Proof systems allow a weak verifier to ascertain the correctness of complex computational statements. Efficiently-verifiable proof systems are fundamental objects in the study of computation, and have led to some of the deepest an...
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Información proyecto VERICOMP
Duración del proyecto: 72 meses
Fecha Inicio: 2018-12-13
Fecha Fin: 2024-12-31
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
Proof systems allow a weak verifier to ascertain the correctness of complex computational statements. Efficiently-verifiable proof systems are fundamental objects in the study of computation, and have led to some of the deepest and most celebrated insights in cryptography and in complexity theory.
The vast and rich literature on proof systems focuses primarily on proving the correctness of intractable statements, e.g. ones that are NP-complete. While the verification can be efficient, the proofs themselves cannot be generated in polynomial time. This limits the applicability of such proof systems, both from a theoretical perspective and in their real-world impact. This proposal aims to obtain a comprehensive understanding of proof systems with polynomial-time proof generation, to explore their practical applicability, and to investigate their connections with foundational questions in cryptography and in complexity theory.
Our study will focus primarily on interactive proof systems for tractable computations. The proposed research aims to revolutionize our understanding of these foundational objects by providing a complete and tight characterization of the complexity or proving and verifying general statements, by achieving breakthroughs in the study of related proof system notions, such as cryptographic arguments, and by building a fine-grained algorithmic theory of proof systems for central polynomial-time computational problems.
Our research will leverage these advances towards diverse applications: from real-world security challenges, such as verifying the correctness of computations performed by the cloud and cryptographic proofs of work, to a complexity-theoretic understanding of the complexity of approximating problems in P and of solving them on random instances.