An enhanced model for preventing guilt agents and providing data security in distributed environment

Data security refers to protective digital privacy measures that are applied to prevent unauthorized access to computers, databases and websites. Big data presents a tremendous opportunity for enterprises across industries. Without the right security and encryption solution in place, however, big data can mean big problems. To find a solution to this problem we propose a model with the ability to trace and prevent unauthorised users from accessing the cluster again. We make use of the LD (Leakage Detector) algorithm during this process to identify the guilt agent responsible for data leakage. We also introduce a Logger which helps to provide unique id to each user and keep a track of the activities performed by them during the whole session. This model will ultimately improve the existing security issues related to data security in Hadoop framework.