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Authors: Yi Hu ; Rubaiyat Hossain ; Papa Seye and Sri Vasireddy

Affiliation: Northern Kentucky University, United States

Keyword(s): Intrusion Detection, Data Mining, Data Exfiltration, Insider Attack

Abstract: This paper illustrates a novel approach for identifying data exfiltration activities by mining Microsoft Windows Registry. It often takes outsider attackers a significant amount of efforts to identify the vulnerabilities in the system or applications and launch the exploit payloads to compromise a system. However insider attackers with legitimate access control privileges can easily steal data and sell data to a third party. Many companies spend lots of money defending network perimeters and applications from outsider attacks but only pay little attention to the insider threat. Although there are existing research efforts ad-dressing various aspects of insider attacks, little research focuses on data exfil-tration detection. The proposed model in this paper employs a data mining method to profile USB device usage patterns and uses various statistical methods to identify anomalous USB device usages. The effectiveness of the model was tested with USB access history extracted from the W indows Registry. (More)

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Paper citation in several formats:
Hu, Y.; Hossain, R.; Seye, P. and Vasireddy, S. (2012). Mining Windows Registry for Data Exfiltration Detection. In Proceedings of the 9th International Workshop on Security in Information Systems - WOSIS, (ICEIS 2012) ISBN 978-989-8565-15-0, pages 101-108. DOI: 10.5220/0004100101010108

@conference{wosis12,
author={Yi Hu. and Rubaiyat Hossain. and Papa Seye. and Sri Vasireddy.},
title={Mining Windows Registry for Data Exfiltration Detection},
booktitle={Proceedings of the 9th International Workshop on Security in Information Systems - WOSIS, (ICEIS 2012)},
year={2012},
pages={101-108},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004100101010108},
isbn={978-989-8565-15-0},
}

TY - CONF

JO - Proceedings of the 9th International Workshop on Security in Information Systems - WOSIS, (ICEIS 2012)
TI - Mining Windows Registry for Data Exfiltration Detection
SN - 978-989-8565-15-0
AU - Hu, Y.
AU - Hossain, R.
AU - Seye, P.
AU - Vasireddy, S.
PY - 2012
SP - 101
EP - 108
DO - 10.5220/0004100101010108

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