A computational model and multi-agent simulation for information assurance
Approved for public release, distribution is unlimited. === This dissertation introduces a computational model of IA called the Social-Technical Information Assurance Model (STIAM). STIAM models organizations, information infrastructures, and human actors as a complex adaptive system. STIAM provides...
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Monterey, California. Naval Postgraduate School.
2012
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ndltd-nps.edu-oai-calhoun.nps.edu-10945-97832015-02-11T03:55:38Z A computational model and multi-agent simulation for information assurance VanPutte, Michael A. Irvine, Cynthia Computer Science Approved for public release, distribution is unlimited. This dissertation introduces a computational model of IA called the Social-Technical Information Assurance Model (STIAM). STIAM models organizations, information infrastructures, and human actors as a complex adaptive system. STIAM provides a structured approach to express organizational IA issues and a graphical notation for depicting the elements and interactions. The model can be implemented in a computational system to discover possible adaptive behavior in an IA environment. A multi-agent simulation is presented that introduces several innovations in multi-agent systems including iconnectors, a biologically inspired visual language and mechanism for inter-agent communications. The computational model and simulation demonstrate how complex societies of autonomous entities interact. STIAM can be implemented as a hypothesis generator for scenario development in computer network defensive mechanisms. 2012-08-22T15:30:06Z 2012-08-22T15:30:06Z 2002-06 http://hdl.handle.net/10945/9783 This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, it may not be copyrighted. Monterey, California. Naval Postgraduate School. |
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description |
Approved for public release, distribution is unlimited. === This dissertation introduces a computational model of IA called the Social-Technical Information Assurance Model (STIAM). STIAM models organizations, information infrastructures, and human actors as a complex adaptive system. STIAM provides a structured approach to express organizational IA issues and a graphical notation for depicting the elements and interactions. The model can be implemented in a computational system to discover possible adaptive behavior in an IA environment. A multi-agent simulation is presented that introduces several innovations in multi-agent systems including iconnectors, a biologically inspired visual language and mechanism for inter-agent communications. The computational model and simulation demonstrate how complex societies of autonomous entities interact. STIAM can be implemented as a hypothesis generator for scenario development in computer network defensive mechanisms. |
author2 |
Irvine, Cynthia |
author_facet |
Irvine, Cynthia VanPutte, Michael A. |
author |
VanPutte, Michael A. |
spellingShingle |
VanPutte, Michael A. A computational model and multi-agent simulation for information assurance |
author_sort |
VanPutte, Michael A. |
title |
A computational model and multi-agent simulation for information assurance |
title_short |
A computational model and multi-agent simulation for information assurance |
title_full |
A computational model and multi-agent simulation for information assurance |
title_fullStr |
A computational model and multi-agent simulation for information assurance |
title_full_unstemmed |
A computational model and multi-agent simulation for information assurance |
title_sort |
computational model and multi-agent simulation for information assurance |
publisher |
Monterey, California. Naval Postgraduate School. |
publishDate |
2012 |
url |
http://hdl.handle.net/10945/9783 |
work_keys_str_mv |
AT vanputtemichaela acomputationalmodelandmultiagentsimulationforinformationassurance AT vanputtemichaela computationalmodelandmultiagentsimulationforinformationassurance |
_version_ |
1716730524583591936 |