Robust authenticated key exchange using passwords and identity-based signatures

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Abstract

In the paper we propose new authenticated key exchange (AKE) protocols from a combination of identity-based signature (IBS) and a password-based authentication. The proposed protocols allows for a client to execute a convenient authentication by using only a humanmemorable password and a server’s identity. The use of an IBS gives security enhancements against threats from password leakage. A server authentication method is based on an IBS, which is independent of a password shared with a client. Even if a password is revealed on the side of a client protected poorly, server impersonation can be prevented effectively. In addition, our protocols have resilience to server compromise by using ‘password verification data’, not a true password at the server. An adversary cannot use the data revealed from server compromise directly to impersonate a client without additional off-line dictionary attacks. We emphasize that most of existing password-based AKE protocols are vulnerable to subsequent attacks after password leakage. Our first hybrid AKE protocol is constructed using concrete parameters from discrete logarithm based groups. It is designed to give resilience to server compromise. Our second protocol is a simplified version of the first protocol where the computation cost of a client is cheap. Generalizing the basic protocols, we present a modular method to convert Diffie-Hellman key exchange into an AKE protocol based on a password and an IBS. Finally, we give performance analysis for our protocols and comparison among known hybrid AKE protocols and ours. As shown later in the paper, our protocols provide better performance. Our experimental results show that the proposed protocols run in at most 20 ms. They can be widely applied for information security applications.

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APA

Hwang, J. Y., Kim, S. H., Choi, D., Jin, S. H., & Song, B. (2015). Robust authenticated key exchange using passwords and identity-based signatures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9497, pp. 43–69). Springer Verlag. https://doi.org/10.1007/978-3-319-27152-1_3

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