Open AccessAn Enhanced Technique to discover web data extraction and Data mining in Multi Cloud Server
Author(s) -
S.Suryanarayana Raju and Ajay Dilip Kumar Marapatla Dadi Madhu SivaRama Krishna
Publication year - 2021
Publication title -
international journal of modern trends in science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-3778
DOI - 10.46501/ijmtst0710006
Subject(s) - computer science , encryption , cloud computing , data mining , cluster analysis , server , knowledge extraction , precision and recall , process (computing) , data extraction , database , information retrieval , world wide web , computer security , machine learning , medline , political science , law , operating system
Data mining is a critical stage in the Knowledge Discovery process acquire from databases (KDD), thus a new approach that’s canjoint with online data process of extraction, which serves as data gathering from the global network ( web), and data miningtechniques is required.The primary contribution of this study is the proposal of a system for collecting categorical online data onseveral cloud servers while ensuring data security and integrity for consumers. The algorithms' effectiveness employed inside ourtechnique is illustrated using clustered sections of the data that should be encrypted inside the cloud server combining the threeclustering measurements precision, recall, and accuracy. We proposed KeyGen algorithm to maintain data security by usingcryptographic concepts with respective ABE (attribute-based encryption) and cypher text policy (cypher text policy) are two typesof attribute-based encryption (CP-ABE).