2026-09-19T04:27:16Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/664092022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Barbara H. Liskov.
Blankstein, Aaron (Aaron M.)
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2011-10-17T21:22:48Z
2011-10-17T21:22:48Z
2011
2011
http://hdl.handle.net/1721.1/66409
755089245
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 71-73).
This thesis presents the design and implementation of an analysis system for audit trails generated by Aeolus, a distributed security platform based on information flow control. Previous work focused on collecting these audit trails in the form of event logs. This thesis presents a model for representing these events and a system for analyzing them. In addition to allowing users to issue SQL queries over the audit log, this analysis system provides mechanisms for active monitoring of events. This thesis introduces a new model for event monitoring called watchers. These watchers receive updates about events from a watcher manager. This manager allows watchers to specify filters and rules for dynamically modifying those filters. My results show that this analysis system can efficiently process large event logs and manage large sets of queries.
by Aaron Blankstein.
M.Eng.
73 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
copyright. They may be viewed from this source for any purpose, but
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Analyzing audit trails in the Aeolus security platform
Analyzing audit trails in the Aeolus
Thesis
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<Abstract>This thesis presents the design and implementation of an analysis system for audit trails generated by Aeolus, a distributed security platform based on information flow control. Previous work focused on collecting these audit trails in the form of event logs. This thesis presents a model for representing these events and a system for analyzing them. In addition to allowing users to issue SQL queries over the audit log, this analysis system provides mechanisms for active monitoring of events. This thesis introduces a new model for event monitoring called watchers. These watchers receive updates about events from a watcher manager. This manager allows watchers to specify filters and rules for dynamically modifying those filters. My results show that this analysis system can efficiently process large event logs and manage large sets of queries.</Abstract>
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