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Guilty Party Analysis in Data Leakage using Adler Checksum Algorithm

Author(s):

Kriti Sharma , vit university; Umamaheswari .R, vit university; V. Sai Silpa, vit univeristy; B. Teja, vit university; Prof. Deepa N, vit university

Keywords:

Adler Checksum Algorithm, Guilty Party Analysis in Data Leakage

Abstract

Data leakage is the unauthorized transmission of data or information from within an organization to an external destination or recipient. Data leakage is defined as the accidental or intentional distribution of private or sensitive data to an unauthorized entity[1]. Protecting confidential data is so important. In today's fast processing business world, sometimes sensitive data must be handed over to trusted third parties called agents. Suppose for example, a company manager or a distributor of a particular company needs to share the most complicated customer data or any other product data to certain organizations, meanwhile some data is leaked and found in an unauthorized place. The distributor must analyze that the leaked data came from (where) one or more agents. So for this problem we have developed a guilt analysis model using traditional method called watermarking technique in a different way by using checksum. We use AdlerChecksum algorithm for finding the guilt agent. Therefore doing so, the outcome would be leakage detection if it gets leaked.

Other Details

Paper ID: IJSRDV5I21065
Published in: Volume : 5, Issue : 2
Publication Date: 01/05/2017
Page(s): 1734-1736

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