With the rapid development of digital technology, the complexity and diversity of data sources present significant security and privacy challenges. To address these issues, this paper proposes an efficient and verifiable Multi-Server Framework for Secure Information Classification and Storage (MSF-SCS). The framework distributes sensitive data across multiple servers, proposing an opening authority to manage classified information and a semi-honest sanitizer to ensure strong authentication while preserving user anonymity. We formalize the security model of our scheme and prove that it satisfies the no-read rule, no-write rule, and unforgeability. We instantiate the scheme and conduct comprehensive experimental evaluations, which demonstrate that MSF-SCS significantly outperforms traditional architectures in terms of scalability and efficiency, making it particularly suitable for industries with stringent data protection requirements. Future work will focus on further improving the system’s security while maintaining its high performance.