Using Evolutionary Algorithms to Identify Problematic Parameter Settings in Software Configurations

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.

Grantor dc:publisher

Wake Forest University

Year dc:date.issued

2017

Author dc:creator

• Ramirez, Sebastian

• Configuration Management

Language dc:language.iso

en

Handle dc:identifier.uri

http://hdl.handle.net/10339/82218

OAI identifier oai:identifier

oai:wakespace.lib.wfu.edu:10339/82218