In the growing domain of cloud applications, cross-tenant keyword searches are increasingly vital for optimizing data utilization but pose significant privacy and security challenges. Existing solutions primarily target single-tenant environments and are unsuitable for the complexities of multi-tenancy, where independent data owners operate. To address this, we propose a privacy-preserving keyword search solution that ensures verifiability, accountability, and parallel processing for secure multi-tenant operations. The system utilizes Elliptic Curve Cryptography (ECC) for efficient encryption and decryption, with SHA algorithms for deduplication and keyword hashing to ensure data integrity. Verifiability guarantees trustworthy search results, while accountability embeds client identity into keyword-based tokens without compromising privacy. Scalability and efficiency are enhanced through parallel processing by partitioning the inverted index for simultaneous search operations. Formal security analyses confirm the system's robustness against threats, and experiments demonstrate its effectiveness in preserving data privacy and achieving high performance in multi-tenant cloud environments. This approach addresses current limitations and supports secure, collaborative data utilization.

KEYWORDS: Cloud applications, multi-tenancy, cross-tenant keyword search, privacy-preserving, verifiability, accountability, parallel processing, Elliptic Curve Cryptography (ECC), SHA algorithms, encryption, decryption, deduplication, keyword hashing, scalability, data privacy, security, inverted index, formal security analysis, multi-tenant operations, collaborative data utilization.