DATA LEAKAGE CULPRIT DETECTION USING ENCRYPTION TECHNIQUES

Authors

  • Akshay Kulkarni Student, Information Technology, SKNCOE, Pune, India - 411041.
  • Ashwini Wangate Student, Information Technology, SKNCOE, Pune, India - 411041.
  • Nischal Kamble Student, Information Technology, SKNCOE, Pune, India – 411041.
  • Priyanka Chinchole Student, Information Technology, SKNCOE, Pune, India - 411041.

Keywords:

Data leakage.

Abstract

Data leakage is a big challenge as critical organizational data should be protected from unauthorized access. Data leakage is defined as the distribution of private or sensitive data to unauthorized entity accidentally or unintentionally [1]. Sensitive data of companies and organizations includes intellectual property (IP), financial information, patient information, personal credit-card data, and other information depending on the business and the industry. This increases the risk of confidential information falling into unauthorized hands. Whether caused by malicious intent, or an inadvertent mistake, by an insider or outsider, exposed sensitive information can seriously hurt an organization. It is very hard for any system administrator to trace out the data leaker among the system users. It creates a lot many ethical issues in the working environment of the office. In the recent years internet technologies has become the backbone of any business organization. These organizations use this facility to improve their efficiency by transferring data from one location to another. But, there are number of threats in transferring critical organizational data as any culprit employee may public this data. This problem is known as data leakage problem. In the proposed work, we are suggesting a model for data leakage problem. In this model, our aim is to identify the culprit who has leaked the critical organizational data.

References

I. Neeraj Kumar, Vijay Katta, Himanshu Mishra, Hitendra Garg. (2014). Detection of Data Leakage in Cloud Computing Environment. IEEE. Sixth International Conference on Computational Intelligence and Communication Networks.

II. Panagiotis Papadimitriou, Hector Garcia-Molina. (2009). A Model for Data Leakage Detection, IEEE.International Conference on Data Engineering.

III. Panagiotis Papadimitriou, and Hector Garcia-Molina.(2011).Data Leakage Detection, IEEE transactions on knowledge and data engineering.

IV. S.Umamaheswari, H.Arthi Geetha. (2011). Detection of Guilty Agents.IEEE. Proceedings of the National Conference on Innovations in Emerging Technology.

Additional Files

Published

15-03-2016

How to Cite

Akshay Kulkarni, Ashwini Wangate, Nischal Kamble, & Priyanka Chinchole. (2016). DATA LEAKAGE CULPRIT DETECTION USING ENCRYPTION TECHNIQUES . International Education and Research Journal (IERJ), 2(3). Retrieved from https://ierj.in/journal/index.php/ierj/article/view/154