Protecting and Securing Sensitive Data in a Big Data Using Encryption

Autor: Praveen Banasode, Sunita Padmannavar
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: EAI Endorsed Transactions on Smart Cities, Vol 4, Iss 11 (2020)
Druh dokumentu: article
ISSN: 2518-3893
DOI: 10.4108/eai.13-7-2018.163991
Popis: The Transaction data which contains a sensitive data, a program like a android app or a browser, does not adequatelyprotect information such as unique values or related payment information, more or likely a privacy concern. In most of thecases, 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 willpartition the data based on set key value pairs, whereby protecting the raw data using real-time security monitoring. Thedata, which requires an extra protection, needs to be identified, based on that data can be encrypted.
Databáze: Directory of Open Access Journals