Treffer: Design of ChaApache framework for securing Hadoop application in big data.

Hadoop is one of the biggest software structures for distributing the data to compute and handle big data. Big data is a group of composite and enormous datasets that contains a massive amount of data such as real-time data, social media, capabilities of data management, money laundering, and so on. Also, big data is measured as regards terabytes and petabytes. The main issue of the Hadoop application is unauthorized access. There are several existing techniques introduced to secure the data, but they have data errors, malicious attacks, and take a long time to compute. So the author proposed a novel ChaApache framework to secure the Hadoop application from an unauthorized person also to save processing time of data, and reduce the error rate. The main aim of the developed replica is securing data from an unauthorized person or unauthorized access. Moreover, the developed ChaApache framework is implemented in python, and the Hadoop application contains 512 bits of data, and the data are encrypted by four 32 bits. Furthermore, the proposed model is compared with other existing replicas in terms of computation time, resource usage, data sharing rate, encryption speed, and so on. [ABSTRACT FROM AUTHOR]

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