Protection of privacy in big data using SDD framework with DNN

摘要

Privacy and Security of Big Data is of priority topic in the current world scenario as most of the expertise relies on Big Data. Same data is being used by different organizations which impose the risk of privacy breaching of individuals. Distributed systems are used as Big Data need high computational power and large storage. As different resources with different system properties are used, there is a chance of privacy violation. While processing big data, to protect privacy of user, different techniques like data anatomization, data suppression etc. are used. To perform these techniques on big data, it requires more computational power and time. Instead of performing these techniques on entire data, it is advisable to perform on sensitive data items. In previous implementations, sensitive data information is identified statically with the information given by data owner. In this paper, identification of sensitive data items is carried out by sensitive data detection framework where Dynamic Neural Network is used. Security mechanisms are to be implemented on these sensitive items to protect privacy and security of Big Data.