A SURVEY PAPER ON DATA LINEAGE IN MALICIOUS ENVIRONMENTS

Abstract

In this paper contains the fulfillment of Data Lineage in Malicious Environment. A data distributor has given precise data to a set of supposedly trusted agents. Some of the data are leaked and found in an unjustified place. The distributor must assess the likelihood that the crevice data came from one or more agents, as opposed to having been individually gathered by other means. We propose data allocation strategies that improve the probability of identifying crevices. These methods do not build on alterations of the released data. In some cases, we can also implant “realistic but fake” data records to further improve our chances of detecting crevice and identifying the guilty party. While sending data over the network there is lots of illegitimate user trying to get useful information. There should be proper security should be provided to data which is send to network. Now a days smartphones use have been increased rapidly and the applications used in smartphones can get easy access to our confidential information. So for avoiding this we used the data lineage mechanism. We give the fake information to guilty agent. We develop and analyze a novel accountable data transfer protocol between two entities within a malicious environment by building upon oblivious transfer, robust Watermarking, and signature primitives. Finally, we perform an experimental evaluation to demonstrate the practicality of our protocol and apply our framework to the important data leakage scenarios of data outsourcing and social networks. In general, we consider our lineage framework for data transfer, to be an key step towards achieving accountability by design.