Identification of Information Leakage and Guilt Agent by using MAC-IP Binding and Recursive Partitioning Algorithm to Modulate the Uncertainty in the Organization’s Network
B. Raja Koti1, G.V.S. Raj Kumar2, K. Naveen Kumar3
1B. Raja Koti*, Research Scholar, Department of Computer Science and Engineering, GITAM Institute of Technology, GITAM, Visakhapatnam, Andhra Pradesh, India.
2Dr. G. V. S. Raj Kumar, Professor, Department of Computer Science and Engineering, GITAM Institute of Technology, GITAM, Visakhapatnam, Andhra Pradesh, India.
3Dr. K. Naveen Kumar, Asst. Professor, Department of Computer Science and Engineering, GITAM Institute of Technology, GITAM, Visakhapatnam, Andhra Pradesh, India.
Manuscript received on October 11, 2019. | Revised Manuscript received on 23 October, 2019. | Manuscript published on November 10, 2019. | PP: 4091-4096 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4314119119/2019©BEIESP | DOI: 10.35940/ijitee.A3912.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this modern era, all organizations depend on internet and data so, maintaining of all data is done by the third party in large organizations. But in this present on-developing world, one have to share the data inside or outside the organization which incorporates the sensitive data of the venture moreover. Data of the organization have sensitive data which should not share with any others but unfortunately, that data was there in the third party hands so; we need to protect the data and also have to identify the guilt agent. For this, we propose a model that would evaluate and correctly identifies guilt agents, for which a recursive partitioning has been created which is a decision tree that spills data in to the sub partitions and does the easiest way to get alert and at least one specialist or it can autonomously accumulate by some different means. The main intention of the model is to secure sensitive information by recognizing the leakage and distinguish the guilt agent.
Keywords: Information protection, Sensitive Data, Recursive partitioning, Data-Leak Detection, Guilt Agent.
Scope of the Article: Algorithm Engineering