NDLI: An Effective Signature Scheme Based on Tate Pairing for Mobile Business

Content Provider	IEEE Xplore Digital Library
Author	Guangming Dai Maocai Wang Hanping Hu Wu Yun
Copyright Year	2008
Description	Author affiliation: Sch. of Comput., China Univ. of Geosci., Wuhan (Guangming Dai; Maocai Wang)
Abstract	A main concern in the public key distribution is the authenticity of the public key. Authenticating public keys provides assurance to the entity that the received public key corresponds to the sender's identity. A typical approach to guarantee the authentication of the public key holder relies on a trusted agent named Certificate Authority (CA). The signature based CA binds entity's identity ID to the corresponding public key KU. However, in the mobile business system, the CA not only adds the system's complexity but also increase the user charge. Therefore, it is the worst security problem in the mobile business systems that there is no signature so that the non-repudiation service can not effectively be protected. In this paper, an effective signature scheme based on Tate pairing for mobile business is put forward. In the signature scheme, the public key is ID of the mobile user or can be obtained by ID so that the user does not need to access the CA to obtain the public key. This feature is especially desirable for mobile applications such as mobile business, mobile government and mobile police office. Therefore, the signature scheme can effectively provide the non-repudiation service for mobile business.
Starting Page	1
Ending Page	4
File Size	214103
Page Count	4
File Format	PDF
ISBN	9781424421077
DOI	10.1109/WiCom.2008.1135
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Elliptic curves Geology Public key Public key cryptography Elliptic curve cryptography Pattern recognition Security Protection Artificial intelligence Mobile computing
Content Type	Text
Resource Type	Article

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