摘要
车联网(IoV)路况监测需要对用户隐私数据进行传输、存储与分析等处理,因此保障隐私数据安全尤为重要,然而传统的安全解决方案难以同时保障实时计算与数据安全。针对上述问题,设计了两个初始化协议与一个定期报告协议等安全协议,并构建了基于软件防护扩展(SGX)技术的IoV路况监测安全数据处理框架(SDPF)。SDPF利用可信硬件在路侧单元(RSU)内实现隐私数据的明文计算,并通过安全协议和混合加密方案保证框架的高效运行与隐私保护。安全性分析表明,SDPF可抵御窃听、篡改、重放、假冒、回滚等攻击。实验结果表明,SDPF的各项计算操作均为毫秒级,尤其是单车辆的所有数据处理开销低于1 ms。与基于雾计算的车联网隐私保护框架(PFCF)和基于同态加密的云辅助车载自组织网络(VANET)隐私保护框架(PPVF)相比,SDPF的安全设计更加全面,单会话消息长度减少了90%以上,计算时间至少缩短了16.38%。
Internet of Vehicles(IoV)traffic monitoring requires the transmission,storage and analysis of private data of users,making the security guarantee of private data particularly crucial.However,traditional security solutions are often hard to guarantee real-time computing and data security at the same time.To address the above issue,security protocols,including two initialization protocols and a periodic reporting protocol,were designed,and a Software Guard Extensions(SGX)-based IoV traffic monitoring Secure Data Processing Framework(SDPF)was built.In SDPF,the trusted hardware was used to enable the plaintext computation of private data in Road Side Unit(RSU),and efficient operation and privacy protection of the framework were ensured through security protocols and hybrid encryption scheme.Security analysis shows that SDPF is resistant to eavesdropping,tampering,replay,impersonation,rollback,and other attacks.Experiment results show that all computational operations of SDPF are at millisecond level,specifically,all data processing overhead of a single vehicle is less than 1 millisecond.Compared with PFCF(Privacy-preserving Fog Computing Framework for vehicular crowdsensing networks)based on fog computing and PPVF(Privacy-preserving Protocol for Vehicle Feedback in cloud-assisted Vehicular Ad hoc NETwork(VANET))based on homomorphic encryption,SDPF has the security design more comprehensive:the message length of a single session is reduced by more than 90%,and the computational cost is reduced by at least 16.38%.
作者
冯睿琪
王雷蕾
林翔
熊金波
FENG Ruiqi;WANG Leilei;LIN Xiang;XIONG Jinbo(College of Computer and Cyber Security,Fujian Normal University,Fuzhou Fujian 350117,China;Fujian Provincial Key Laboratory of Network Security and Cryptology(Fujian Normal University),Fuzhou Fujian 350007,China)
出处
《计算机应用》
CSCD
北大核心
2023年第6期1870-1877,共8页
journal of Computer Applications
基金
国家自然科学基金资助项目(61872088)。
关键词
车联网
软件防护扩展
路况监测
路侧单元
数据安全
Internet of Vehicles(IoV)
Software Guard Extensions(SGX)
traffic monitoring
Road Side Unit(RSU)
data security