2026-09-21T14:19:29Zhttps://wakespace.lib.wfu.edu/server/oai/requestoai:null:10339/822182026-09-02T10:15:03Zcom_10339_14934col_10339_38132
Ramirez, Sebastian
2017-06-15T08:36:04Z
2017-06-15T08:36:04Z
2017
https://wakespace.lib.wfu.edu/handle/10339/82218
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.
en
Wake Forest University
Configuration Management
Genetic Algorithms
Parameter chains
secure configurations
Using Evolutionary Algorithms to Identify Problematic Parameter Settings in Software Configurations
Thesis
Fulp, Errin W
Cañas, Daniel A
Gage, Howard D
Computer Science
open.access