Analyzing Encrypted Cloud Data With Multiple Keywords Productively For Factories

Cloud storage is quickly becoming the norm in today's online infrastructure because of the low administration costs and convenient accessibility. The cloud storage system offers crucial advantages by letting cloud users keep their massive amounts of data in the cloud. Better performance during data retrieval necessitates attending to the privacy and security of data stored in the cloud. The necessary information can be obtained from the cloud using the current improved semantic feature abstraction method E-TFIDF (Enhanced-Term Frequency-Inverse Document Frequency). There was still no solution for the problem of secure cloud-based data access. Current method SEDFS (Searchable Encrypted Data File Sharing) system applied along with limited and precise keyword quest; indexing procedure necessary for improvement. The research focuses on SHE (Secured Hybrid Search), a method for conducting encrypted multi-keyword searches on cloud platforms. Using a category-based method, an index list is built for each document depending on its classification. Clearly, when compared to both the current system and the adaptively secure SSE technique, it has been found that the proposed approach significantly improves encryption and decryption throughput in the shortest possible time. In addition, the suggested algorithm shortens the amount of time required to index and conduct a search on a variety of documents. There was also a decrease in the amount of time spent searching and indexing, and an increase in the efficiency with which keywords could be extracted.