Keywords and Phrases
Insider threat detection; Intrustion Detection Systems
"Insider threat detection is a major problem. Studies show that the extent of damage that could be caused by insiders is much more extensive than attacks from outside the organization. Intrusion detection systems in use are not geared to detect these attacks. This is because there is a great deal of overlap between insider behavior and that of the normal user. Moreover, intrusion detection systems are attuned to look for attacks from outside the organization. In distributed systems, the complexity of detecting intrusions is increased due to the difficulty in monitoring and correlating the events that happen in various subsystems. This work investigates insider threats, creation of insider-like attacks and briefly discusses the results of experiments conducted to detect such type of attacks.
In order to study and define, normal and intrusive behavior, a simulation of a network used to transport and stock boots in different centers was used. This is called the Boots system. During restudy functional requirements were added to the security requirements.
There were many insider threats that could not be detected solely by an intrusion detection system. In this study only the insider attacks that leave a paper trial and have some means of detection were considered"--Abstract, page iii.
Miller, Ann K.
McMillin, Bruce M.
Stanley, R. Joe
Electrical and Computer Engineering
M.S. in Computer Engineering
University of Missouri--Rolla
viii, 51 pages
© 2003 Krishna Prasad Balasubramanian, All rights reserved.
Thesis - Restricted Access
Computer networks -- Security measures
Print OCLC #
Link to Catalog Record
Electronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.http://merlin.lib.umsystem.edu/record=b5071975~S5
Balasubramanian, Krishna Prasad, "Insider attack scenarios and black box testing in support of insider threat detection" (2003). Masters Theses. 2381.
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