Open AccessEnhanced Cyber Security for Big Data Challenges
Author(s) -
S. Padmapriya,
N. Partheeban,
N. Kamal,
A. Suresh,
S. Arun
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.j9729.0881019
Subject(s) - big data , computer science , computer security , cloud computing , social media , information sensitivity , internet privacy , data science , world wide web , data mining , operating system
In recent years mining of data from social media is attracting more attention due to the explosion in the growth of Big Data. In security, Big Data deals with collection of huge digital information for analyzing, visualizing and to draw the insights for the prediction & prevention of cyber attacks. The Big Data mined about an enterprise from the data cloud, if properly analyzed reveals the private information which is highly risky. Maintaining the privacy of users of social media is the major challenge with respect to the security issues. As the data is generally stored in a data cloud, a boundary of trust must be established between the social media users and the data bank owners. Hence there is requirement of developing an efficient protocol for sharing of data. To secure the sensitive information of the user, data mining can be used along with an effective algorithm. This paper proposes the technique of code inline parsing to make the data more secure from the attacks & cyber hacks along with the SQL injections such that the data on the social media is secured. The proposed method secures the platform of Big Data which protects the user’s sensitive information.