• Karthi P
• Dr.Menaka S.R
• Dr.Singaravel G3

Data owners are under pressure to move their intricate on-premises data management systems to private cloud providers in order to take advantage of more flexibility and reduced costs since the emergence of cloud computing. Sensitive data must first be encrypted before being outsourced to ensure data privacy. The renders the conventional method of utilizing data, which is predicated on unencrypted keyword searches, antiquated. Therefore, it is imperative to activate an encrypted cloud data search service. In order to meet the effective data retrieval need, search services must support multi-keyword queries and offer result similarity rating, given the volume of data users and documents maintained in cloud storage. Comparable works on searchable encryption seldom distinguish betIen search results and concentrate on single term or Boolean keyword search. In The work, I identify and solve the hard problem of multi-keyword ranked search over encrypted cloud data (MRSE) with privacy preservation for the first time. I also outline a strict set of privacy requirements that must be met in order to put such a safe cloud data consumption system into place.

Machine Learning, Fault Prediction, Fuzzy Convolution Neural Network (FCNN), Heterogeneous Sensing Data Fusion

"ENHANCING CLOUD DATA SECURITY AND ACCESS CONTROL AN EFFICIENT AUDITING SCHEME ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.i360-i366, June-2024, Available :http://www.jetir.org/papers/JETIR2406837.pdf

"ENHANCING CLOUD DATA SECURITY AND ACCESS CONTROL AN EFFICIENT AUDITING SCHEME ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. ppi360-i366, June-2024, Available at : http://www.jetir.org/papers/JETIR2406837.pdf