Experimental Evaluation of a Secured Phrase Searching Model Using Cipher Principles Over Cloud Computing Platform
R. Vijaya Geetha, M. Kanniga Parameshwari, V. Praveena, T. Venkatesan, Meena Sindhu, S. Bhuvana · 2024
For many cloud-based IoT device learning applications, including sensible clinical data analytics, phrase search—which allows retrieval of files containing a given term—plays a crucial role. In order to prevent sensitive information from being exposed by third-party providers, data owners typically encrypt files (such as medical records) before sending them to the cloud. Having said that, this does make the search operation quite challenging and current searchable encryption systems for multiple keyword searches can't do word searches because they can't determine the location connection of multiple key phrases in a query word using encrypted data stored on the cloud server side. This study presents a model called MCLPS, which stands for “Modified Cyber Law for Phrase Searching.” Its purpose is to identify specific phrases in a cloud environment. To test how well the model works, it is cross-validated with the traditional BET. The safety of information in the cloud has long been an important concern for cloud service providers and their clients, despite the fact that there are several elements that could affect data security during searches. The reason behind this is the presence of dangers posed by both external data sources and internal partners, namely, their employees. Therefore, due to its massive structure, maintaining this security perfect is an ongoing headache and difficult effort in the cloud. In most cases, this is achieved by encrypting data at all times and taking extra precautions to ensure that data is not compromised during the audition or any other internal exercises. For safe phrase search in cloud IoT, this study suggested the MCLPS model and the BET encryption technique. The data integration, recovery, indexing, sliding, encryption, decryption, and transfer processes are all encompassed in the suggested works. This proposed study introduces a new approach to encrypted searching that allows encrypted phrase searches, and the MCLPS ad BET procedures was developed to secure large data sets before storing them in the cloud.