Development of Big data anonymization framework using DNA Computing

A widely used term; privacy-preserving data mining has a variety of applications that may theoretically be considered “privacy violating.” The most important thing is to develop techniques that are trustworthy and likely to work without compromising security. The anonymization of structured data is the primary emphasis of traditional approaches, whereas unstructured and streaming data are the main topics of modern research. Another issue is the storing of enormous amounts of data. In this paper we propose a framework for anonymizing massive data while utilizing DNA computing, a future-proof storage method. Frist, we implement anonymization algorithms for structured and unstructured data by preserving privacy of sensitive information. Secondly, we implement DNA computing techniques to store and retrieve huge amount of published data in the DNA storage using Hadoop eco-system and MapReduce paradigm for data storage. Finally, we generate appropriate DNA flat file format of the anonymous data to store in the DNA storage. In the process of DNA computing, we develop genetic based algorithms to encode and decode the anonymous data to comply with the DNA sequence format. The artificially synthesized DNA sequence of digital data is so forth processed and stored into a DNA molecule and retrieved back on request.