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Find me: A User Friendly Key Logger Tool for Insider Threat Identification

J. Dhiviya Rose1 , Vishal Kumar2 , Amit Singh Khinchee3 , Tushar Rathee4 , Keerthivardhan A.5

Section:Research Paper, Product Type: Journal-Paper
Vol.9 , Issue.6 , pp.115-120, Dec-2021


Online published on Dec 31, 2021


Copyright © J. Dhiviya Rose, Vishal Kumar, Amit Singh Khinchee, Tushar Rathee, Keerthivardhan A. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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IEEE Style Citation: J. Dhiviya Rose, Vishal Kumar, Amit Singh Khinchee, Tushar Rathee, Keerthivardhan A., “Find me: A User Friendly Key Logger Tool for Insider Threat Identification,” International Journal of Scientific Research in Computer Science and Engineering, Vol.9, Issue.6, pp.115-120, 2021.

MLA Style Citation: J. Dhiviya Rose, Vishal Kumar, Amit Singh Khinchee, Tushar Rathee, Keerthivardhan A. "Find me: A User Friendly Key Logger Tool for Insider Threat Identification." International Journal of Scientific Research in Computer Science and Engineering 9.6 (2021): 115-120.

APA Style Citation: J. Dhiviya Rose, Vishal Kumar, Amit Singh Khinchee, Tushar Rathee, Keerthivardhan A., (2021). Find me: A User Friendly Key Logger Tool for Insider Threat Identification. International Journal of Scientific Research in Computer Science and Engineering, 9(6), 115-120.

BibTex Style Citation:
@article{Rose_2021,
author = {J. Dhiviya Rose, Vishal Kumar, Amit Singh Khinchee, Tushar Rathee, Keerthivardhan A.},
title = {Find me: A User Friendly Key Logger Tool for Insider Threat Identification},
journal = {International Journal of Scientific Research in Computer Science and Engineering},
issue_date = {12 2021},
volume = {9},
Issue = {6},
month = {12},
year = {2021},
issn = {2347-2693},
pages = {115-120},
url = {https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=2616},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=2616
TI - Find me: A User Friendly Key Logger Tool for Insider Threat Identification
T2 - International Journal of Scientific Research in Computer Science and Engineering
AU - J. Dhiviya Rose, Vishal Kumar, Amit Singh Khinchee, Tushar Rathee, Keerthivardhan A.
PY - 2021
DA - 2021/12/31
PB - IJCSE, Indore, INDIA
SP - 115-120
IS - 6
VL - 9
SN - 2347-2693
ER -

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Abstract :
Insider Threat Detection has become one of the lime lights that are a widely accepted issue that reflects a growing concern in security communities. Insider Threats are listed as the malicious activities performed by authorized users in any organization resulting in various damages like intellectual property loss and breach of security details. The increasing insider threads have made the organizations turn their focus to various ‘malicious insiders’: the own people who work not in favor of the organization`s growth. Moreover, an insider, additionally viewed as a worker of an organization, turns into a threat when the aim or activity, intention can influence the organization contrarily. The insider threat has been a famous issue in associations that have brought about the deficiency of trust, secret information, and data. Although many insider attacks have more privilege and legitimate access to information in comparison to external attacks which can cause much damage to the organization, the internal threats can cause extensive damage. This project aims to offer a tool that helps in Insider Threat Detection by detecting similar data of the database using java. The Keylogger detects the abnormal behavior of the user using correlating the data movement as a keylogger installed in all systems organizations for monitoring the keystrokes activities of the employee system. After matching the Keystrokes with sensitive keywords, the system generates an alert log to warn relevant IT cells of the organization when the user accesses extraordinary, confidential data after comparing its system database.

Key-Words / Index Term :
Insider Attack; Malicious insiders; Authorized users; Keylogger; Insider Threat Detection

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