姚念民

个人信息Personal Information

教授

博士生导师

硕士生导师

任职 : 智能计算教研室主任

性别:男

毕业院校:吉林大学

学位:博士

所在单位:计算机科学与技术学院

学科:计算机应用技术. 计算机软件与理论

办公地点:创新园大厦A820

联系方式:13304609362

电子邮箱:lucos@dlut.edu.cn

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LIAP: A local identity-based anonymous message authentication protocol in VANETs

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论文类型:期刊论文

发表时间:2017-11-01

发表刊物:COMPUTER COMMUNICATIONS

收录刊物:Scopus、SCIE、EI

卷号:112

页面范围:154-164

ISSN号:0140-3664

关键字:Identity signature; PKI certificate; Revocation; Authentication; VANETs

摘要:In vehicular ad hoc networks (VANETs), vehicle communicates with other. nodes through an open wireless channel, which raises many potential safety issues. Both the public key infrastructure (PKI) and identity based authentication protocols can meet the requirements of security and privacy of VANETs. However, the receiver needs to check certificate revocation list (CRL) before certificate and signature verification in PKI-base schemes. The additional CRL checking reduces the authentication efficiency. In the identity based schemes, every vehicle holds too many valid identities in order to protect privacy. It is complicated to revoke the membership of vehicle. To cope with the inherent issues, we propose a local identity based anonymous message authentication protocol (LIAP) for VANETs, in which each vehicle and road side unit (RSU) is assigned a unique long term certification from the certificate authority (CA) in registration phase. RSU is in charge of managing and assigning the local master keys to every vehicle of entering its communication range. When vehicle meets a new RSU, they authenticate each other by their long certificates. The valid vehicle can obtain the local master keys from current RSU to generate the localized anonymous identity. To protect privacy, vehicle randomly chooses the anonymous identity to sign the safety-related message, which can be efficiently verified by the single or batch authentication manner. Finally, performance analysis and simulation show that LIAP is effective in terms of authentication speed and communication overhead. (C) 2017 Elsevier B.V. All rights reserved.