2026-09-20T14:54:50Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/16177 2023-07-10 col_2142_8888 col_2142_5131 com_2142_8887 com_2142_234 com_2142_5130

Copyright 2010 Suraj Nellikar Insider threat Insider detection algorithms Role-based access control Nicol, David M. Nellikar, Suraj 2010-05-19T18:39:53Z 2010-05-19T18:39:53Z 2010-05-19T18:39:53Z Insider threat problems are widespread in industry today. They have resulted in huge losses to organizations. The security reports by leading organizations point out the fact that there have been many more insider attacks in recent years than any other form of attack. Detection of these insider threats is a top priority. One problem facing the detection mechanisms is that the real data for modeling is not easily available. This thesis describes a simulator which can simulate the insiders and generate access information in the form of logs. Currently there are many methods which use data mining algorithms to detect insider attacks. Role based detection is a well known mechanism to accurately distinguish insider behavior from the normal behavior. The thesis focuses on the advantages of using role based mechanisms for insider threat detection. Five algorithms have been chosen and performance analysis of these under various scenarios is carried out. The thesis discusses these results in detail. The simulator is built on the Scalable Simulation Framework (SSF). It is an extension of the Boeing simulator, JANUS. The simulator uses behavior files to model an insider/normal user and generates the access information using Markov chains. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2010-04-27T21:08:44Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 Nellikar_Suraj.doc: 1567744 bytes, checksum: 4a130af31f941d4b6ba383daf28cbf9a (MD5) Nellikar_Suraj.pdf: 1322399 bytes, checksum: 5bbe62233246b6f8243c424518cfa684 (MD5) Made available in DSpace on 2010-05-19T18:39:53Z (GMT). No. of bitstreams: 3 Nellikar_Suraj.doc: 1567744 bytes, checksum: 4a130af31f941d4b6ba383daf28cbf9a (MD5) Nellikar_Suraj.pdf: 1322399 bytes, checksum: 5bbe62233246b6f8243c424518cfa684 (MD5) license.txt: 4064 bytes, checksum: c594c3de8066034506bc0fcc77299238 (MD5) http://hdl.handle.net/2142/16177 en Insider threat simulation and performance analysis of insider detection algorithms with role based models 2010-5 Electrical & Computer Eng 1933 Electrical & Computer Engr 1200 University of Illinois at Urbana-Champaign Thesis M.S. MS:Electr & Computer Eng-UIUC 10KS1200MS