While cloud computing offers several benefits, it has also raised privacy and security problems, which have piqued the attention of researchers in the field. One of the main issues in this field is the storage and accessibility of sensitive records. Research on methods to decipher encrypted files kept on distant cloud servers has attracted a lot of attention from academics. There have been a lot of proposals for methods to do conjunctive keyword searches, but fewer for methods that are more targeted. In this study, we provide a Bloom filterbased phrase search method that outperforms state-of-the-art methods while maintaining or improving upon storage and transmission costs. To back up the functionality, our method employs a sequence of n-gram filters. The technique is flexible enough to withstand inclusion-relation assaults and displays a trade-off between storage and false positive rate. It also details a design method that takes into account the desired false positive