Digital Library
Insider Threat Control: Using Plagiarism Detection Algorithms to Prevent Data Exfiltration in Near Real Time
- October 2013
- In this report, the authors describe how an insider threat control can monitor an organization's web request traffic for text-based data exfiltration.
- Insider Threat
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Publisher: Software Engineering Institute
CMU/SEI Report Number: CMU/SEI-2013-TN-008
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Abstract
In organizations with access to the internet, the potential for data leakage is ever present. Data loss prevention is a difficult issue because exfiltration channels, such as modern webmail services, are readily available to insiders. An insider can paste text into a webmail message to bypass other controls. Therefore, monitoring must include the content of this communication. A data loss prevention control determines if the content in outgoing web requests is similar to the organization's intellectual property, actively blocks suspicious requests, and logs these events. This technical note describes how a control can monitor web request traffic for text-based data exfiltration attempts and block them in real time. Using this control can help an organization protect text-based intellectual property, including source code repositories.
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Cite This Report
SEI
Lewellen, Todd; Silowash, George; & Costa, Daniel. Insider Threat Control: Using Plagiarism Detection Algorithms to Prevent Data Exfiltration in Near Real Time. CMU/SEI-2013-TN-008. Software Engineering Institute, Carnegie Mellon University. 2013. http://resources.sei.cmu.edu/library/asset-view.cfm?AssetID=64680
IEEE
Lewellen. Todd, Silowash. George, and Costa. Daniel, "Insider Threat Control: Using Plagiarism Detection Algorithms to Prevent Data Exfiltration in Near Real Time," Software Engineering Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, Technical Note CMU/SEI-2013-TN-008, 2013. http://resources.sei.cmu.edu/library/asset-view.cfm?AssetID=64680
APA
Lewellen, Todd., Silowash, George., & Costa, Daniel. (2013). Insider Threat Control: Using Plagiarism Detection Algorithms to Prevent Data Exfiltration in Near Real Time (CMU/SEI-2013-TN-008). Retrieved December 11, 2018, from the Software Engineering Institute, Carnegie Mellon University website: http://resources.sei.cmu.edu/library/asset-view.cfm?AssetID=64680
CHI
Todd Lewellen, George Silowash, & Daniel Costa. Insider Threat Control: Using Plagiarism Detection Algorithms to Prevent Data Exfiltration in Near Real Time (CMU/SEI-2013-TN-008). Pittsburgh, PA: Software Engineering Institute, Carnegie Mellon University, 2013. http://resources.sei.cmu.edu/library/asset-view.cfm?AssetID=64680
MLA
Lewellen, Todd., Silowash, George., & Costa, Daniel. 2013. Insider Threat Control: Using Plagiarism Detection Algorithms to Prevent Data Exfiltration in Near Real Time (Technical Report CMU/SEI-2013-TN-008). Pittsburgh: Software Engineering Institute, Carnegie Mellon University. http://resources.sei.cmu.edu/library/asset-view.cfm?AssetID=64680
BibTex
@techreport{LewellenInsiderThreat2013,
title={Insider Threat Control: Using Plagiarism Detection Algorithms to Prevent Data Exfiltration in Near Real Time},
author={Todd Lewellen and George Silowash and Daniel Costa},
year={2013},
number={CMU/SEI-2013-TN-008},
institution={Software Engineering Institute, Carnegie Mellon University},
address={Pittsburgh, PA},
url={http://resources.sei.cmu.edu/library/asset-view.cfm?AssetID=64680}
}