Identity-embedding method for decentralized public-key infrastructure

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Abstract

A public key infrastructure (PKI) is for facilitating the authentication and distribution of public keys. Currently, the most commonly employed approach to PKI is to rely on certificate authorities (CAs), but recently there has been arising more need for decentralized peer-to-peer certification like Webs of Trust. In this paper, we propose an identity-embedding method suitable for decentralized PKI. By embed- ding not only ID of the candidate public-key owner itself but also IDs of his guarantors into PK, we can construct Web of guarantors on public keys. Here guarantors can be chosen arbitrarily by the candidate public- key owner. Our embedding method uses a combination of two public-key cryptosystems; the first cryptosystem is for PKI directly. Here we employ a technique to embed a string into a public key of the first cryptosystem. As such a string, we choose a concatenation of ID of a candidate public-key owner, IDs of his guarantors, and a public key of the second cryptosystem. This embedded public key of the second cryptosystem is used by the candidate public-key owner that he certainly knows the secret key that corresponds to the public key of the first cryptosystem. Then, with an aid of a broadcast mechanism of an updated public-key list on a peer-to-peer network, we can attain the decentralized PKI. Such an embedding method is concretely realized by the RSA encryption with the Lenstra’s algorithm, which can be used as the first cryptosystem. As the second cryptosystem, we employ an elliptic curve encryption whose security is equivalent to the security of the RSA encryption, where the former achieves shorter key size than the latter. We write down concrete values of parameters for a realization of the embedding.

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APA

Anada, H., Kawamoto, J., Weng, J., & Sakurai, K. (2015). Identity-embedding method for decentralized public-key infrastructure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9473, pp. 1–14). Springer Verlag. https://doi.org/10.1007/978-3-319-27998-5_1

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