Concurrent knowledge extraction in the public-key model

3Citations
Citations of this article
18Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Knowledge extraction is a fundamental notion, modeling machine possession of values (witnesses) in a computational complexity sense and enabling one to argue about the internal state of a party in a protocol without probing its internal secret state. However, when transactions are concurrent (e.g., over the Internet) with players possessing public-keys (as is common in cryptography), assuring that entities "know" what they claim to know, where adversaries may be well coordinated across different transactions, turns out to be much more subtle and in need of re-examination. Here, we investigate how to formally treat knowledge possession by parties (with registered public-keys) interacting over the Internet. Stated more technically, we look into the relative power of the notion of "concurrent knowledge-extraction" (CKE) in the concurrent zero-knowledge (CZK) bare public-key (BPK) model where statements being proven can be dynamically and adaptively chosen by the prover. We show the potential vulnerability of man-in-the-middle (MIM) attacks turn out to be a real security threat to existing natural protocols running concurrently in the public-key model, which motivates us to introduce and formalize the notion of CKE, alone with clarifications of various subtleties. Then, both generic (based on standard polynomial assumptions), and efficient (employing complexity leveraging in a novel way) implementations for NP are presented for constant-round (in particular, round-optimal) concurrently knowledge-extractable concurrent zero-knowledge (CZK-CKE) arguments in the BPK model. The efficient implementation can be further practically instantiated for specific number-theoretic language. © 2010 Springer-Verlag Berlin Heidelberg.

Cite

CITATION STYLE

APA

Yao, A. C., Yung, M., & Zhao, Y. (2010). Concurrent knowledge extraction in the public-key model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6198 LNCS, pp. 702–714). https://doi.org/10.1007/978-3-642-14165-2_59

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free