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%.