The Transaction data which contains a sensitive data, a program like a android app or a browser, does not adequately protect information such as unique values or related payment information, more or likely a privacy concern. In most of the cases, security breaches, which involve the unstructured data like documents and files, will reveal all sensitive information. To address this issue the transaction data can be processed across the nodes based on Advanced Encryption Standard(AES) algorithm for generating keys and also by using MapReduce algorithm to check number of sensitive data, where we will partition the data based on set key value pairs, whereby protecting the raw data using real-time security monitoring. The data, which requires an extra protection, needs to be identified, based on that data can be encrypted.

Big data infrastructure needs to be structured in the most critical aspects and wisely calculate how large data applications are managed in order to achieve the most important security issues required. One of them is privacy is a related feature as users can share more and more personal data and content and public clouds on social networks through their devices and computers. The previous system have some drawbacks, it is not secure the sensitive data storage security of privacy issues in the big data. However, the existing encryption system for data cannot protect the access mode, and it can also leak sensitive information. To overcome the issues in this work proposed the method Transparent Secure Hashing Data Optimized Privacy Protection Encryption (TSHDOPPE) Algorithm for Encryption of data can prevent permission to use the unwanted users' associated data storage system of data. Less storage leakage overhead and efficiency are proposed. It includes stored in a transparent data protected for data at rest and could not leak the Data for data in Transit. Non-relational data storage and protection data storage has been a TSHDOPPE algorithm used to ensure the transaction log. In the data used for stored in cloud computing, managing user data optimizing the Improved Deep Neural Network (IDNN) is reduces difficult and reduces the cost of maintaining data. Unprotected data in Transit or at rest, or vulnerable to attacks, companies are also effective security measures that provide protected data with strong data protection between the device and the network in these conditions.

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