Automated text categorization has been measured as a crucial technique for run and practice a huge quantity of papers in digital appearances that were extensive & constantly growing. In common, text categorization acts a significant responsibility in data mining and summarization, text recovery, and query responding. Interruption recognition scheme plays an vital responsibility in network protection. Intrusion recognition method was a analytical method utilized for forecasting network information collision is common or Intrusion. ML algorithms were utilized to construct exact methods to grouping, categorization & guessing. Labeled text papers were utilized for classify text with supervised categorizations. This article used these classifiers in many types for labeled papers & evaluates correctness to classifiers. An artificial neural network (ANN) method utilizing back propagation network (BPN) is worked by more than a few additional techniques to build a autonomous policy to labeled & supervised text categorization procedure. The obtainable standard mechanism was used for analyzing working of categorization utilizing labeled papers. Investigational examination on actual information discloses for mechanism runs good in stipulations of categorization exactness.

Most popular computation technique in recent days is cloud computing, where we utilizing the virtual computing resources like processing data, and storage. Virtual computing environment is leads the customer lose control on his/her data, to answer this problem cloud computing has auditing techniques by cloud service provider (CSP), Third party auditor (TPA) by remote auditing data (RDA) methods. Cloud storage architectures are single tenant or multi tenant, where we compare the architectures, multi-tenancy cloud storages which contain the serious data privacy problem. To provide an efficient privacy solution for multi-tenancy cloud storage we apply RDA methods belongs to RDA taxonomy. In this paper we propose a technique to provide privacy on customer data on multi-tenant cloud storage with file attribute test.

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