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Using Evolutionary Algorithms to Identify Problematic Parameter Settings in Software Configurations

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title
Using Evolutionary Algorithms to Identify Problematic Parameter Settings in Software Configurations
author
Ramirez, Sebastian
abstract
As software systems become more complex and configurable, failures due to misconfigurations are becoming more common. Many cyber attacks can be attributed to administrators who, unaware of insecure settings or novel attacks, expose vulnerabilities in their systems. The difficulty of diagnosing and fixing misconfigurations is primarily due to the large number of possible configuration parameter settings and the potential existence of interdependencies between them.
subject
Configuration Management
Genetic Algorithms
Parameter chains
secure configurations
contributor
Fulp, Errin W (committee chair)
Cañas, Daniel A (committee member)
Gage, Howard D (committee member)
date
2017-06-15T08:36:04Z (accessioned)
2017-06-15T08:36:04Z (available)
2017 (issued)
degree
Computer Science (discipline)
identifier
http://hdl.handle.net/10339/82218 (uri)
language
en (iso)
publisher
Wake Forest University
type
Thesis

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