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- W3118132313 abstract "We present a process utilizing an evolutionary learning method to explore combinations of security mechanisms with regard to performance problems they might create for a particular user profile. For each combination, the process uses an evolutionary search to identify sequences of interactions with a computer (in form of a virtual machine) that stress the system to a much larger degree with the combination installed than without it. The process then compares the mechanism combinations using the “best sequences” for each combination to suggest the combination that overall has the least impact on performance. The process also explores interaction sequences that caused system failure, or were not able to finish within the given time limit, to identify incompatibilities between security mechanisms. For evaluation, the process was applied to create a tool for finding the best set of multiple anti-virus software systems for Windows XP. In the primary evaluation, the tool identified a set of five mechanisms that did not degrade performance too far, while providing the intended security coverage. At the same time, the tool found a clear incompatibility between two mechanisms as demonstrated by a zip operation failure after only a few interactions." @default.
- W3118132313 created "2021-01-05" @default.
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- W3118132313 date "2020-11-01" @default.
- W3118132313 modified "2023-09-26" @default.
- W3118132313 title "Decision Support for Combining Security Mechanisms using Exploratory Evolutionary Testing" @default.
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- W3118132313 doi "https://doi.org/10.1109/ictai50040.2020.00091" @default.
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