Behavioral Distance for Intrusion Detection
We introduce a notion, behavioral distance, for evaluating the extent to which processes—potentially running different programs and executing on different platforms—behave similarly in response to a common input. We explore behavioral distance as a means to detect an attack on one process that cause...
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sg-smu-ink.sis_research-22422010-12-22T08:24:06Z Behavioral Distance for Intrusion Detection GAO, Debin Reiter, Michael K. SONG, Dawn We introduce a notion, behavioral distance, for evaluating the extent to which processes—potentially running different programs and executing on different platforms—behave similarly in response to a common input. We explore behavioral distance as a means to detect an attack on one process that causes its behavior to deviate from that of another. We propose a measure of behavioral distance and a realization of this measure using the system calls emitted by processes. Through an empirical evaluation of this measure using three web servers on two different platforms (Linux and Windows), we demonstrate that this approach holds promise for better intrusion detection with moderate overhead. 2005-09-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/1243 info:doi/10.1007/11663812_4 http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.113.7936 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Information Security |
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Information Security GAO, Debin Reiter, Michael K. SONG, Dawn Behavioral Distance for Intrusion Detection |
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We introduce a notion, behavioral distance, for evaluating the extent to which processes—potentially running different programs and executing on different platforms—behave similarly in response to a common input. We explore behavioral distance as a means to detect an attack on one process that causes its behavior to deviate from that of another. We propose a measure of behavioral distance and a realization of this measure using the system calls emitted by processes. Through an empirical evaluation of this measure using three web servers on two different platforms (Linux and Windows), we demonstrate that this approach holds promise for better intrusion detection with moderate overhead. |
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GAO, Debin Reiter, Michael K. SONG, Dawn |
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GAO, Debin Reiter, Michael K. SONG, Dawn |
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GAO, Debin |
title |
Behavioral Distance for Intrusion Detection |
title_short |
Behavioral Distance for Intrusion Detection |
title_full |
Behavioral Distance for Intrusion Detection |
title_fullStr |
Behavioral Distance for Intrusion Detection |
title_full_unstemmed |
Behavioral Distance for Intrusion Detection |
title_sort |
behavioral distance for intrusion detection |
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Institutional Knowledge at Singapore Management University |
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2005 |
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https://ink.library.smu.edu.sg/sis_research/1243 http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.113.7936 |
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