ML-CLSCKS: Module lattice based certificateless signcryption with keyword search in cloud storage

• We proposed ML-CLSCKS to achieve data confidentiality and unforgeability, protecting both the data and authenticity of encrypted information while resists quantum attacks. • The security of ML-CLSCKS proves Module Learning With Errors and Module Short Integer Solution hardness assumptions. • ML-CLSCKS eliminates certificate management and key escrow problems because it is designed based on certificateless cryptography. • ML-CLSCKS shows reduced computational and storage efficiency compared to other existing schemes. • In addition, ML-CLSCKS avoids trapdoor algorithms like TrapGen and SamplePre, improving efficiency. Public Key Authenticated Encryption with Keyword Search (PAEKS) allows keyword searches over encrypted data in the cloud without revealing actual data and the receiver can verify the sender’s authenticity or detect tampering. However, the existing PAEKS schemes are based on classical hard problems that are vulnerable to quantum attacks. To overcome these issues, lattice-based PAEKS schemes have been proposed, which provide post quantum security but incur high computational overhead and suffer from inherent issues such as the Certificate Management Problem (CMP) or Key Escrow Problem (KEP). To address the above problems, in this paper, we introduce a Module Lattice-based Certificateless Signcryption with Keyword Search (ML-CLSCKS), which relies on Module Learning with Errors (MLWE) and Module Short Integer Solution (MSIS). The security analysis proves that ML-CLSCKS achieves both confidentiality and unforgeability against Type I and Type II adversaries in the Random Oracle Model (ROM). The performance analysis shows that ML-CLSCKS outperforms than existing lattice-based PAEKS schemes and makes the practical quantum-resistant scheme suitable for searchable encryption in cloud environments.