Generating behavior-based malware detection models with genetic programming

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@InProceedings{conf/pst/WuchnerOLP16,

• author = "Tobias Wuchner and Martin Ochoa and Enrico Lovat and Alexander Pretschner",
• booktitle = "2016 14th Annual Conference on Privacy, Security and Trust (PST)",
• title = "Generating behavior-based malware detection models with genetic programming",
• year = "2016",
• publisher = "IEEE",
• bibdate = "2017-05-21",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/pst/pst2016.html#WuchnerOLP16",
• pages = "506--511",
• month = "12-14 " # dec,
• address = "Auckland, New Zealand",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-1-5090-4379-8",
• DOI = "doi:10.1109/PST.2016.7907008",
• abstract = "Malware remains a major IT security threat and current detection approaches struggle to cope with a professionalized malware development industry. We propose the use of genetic programming to generate effective and robust malware detection models which we call FrankenMods. These are sets of graph metrics that capture characteristic malware behaviour. Evolution of FrankenMods with good detection capabilities yields continuously improved detection effectiveness. FrankenMods are operationalized by evaluating them on quantitative data flow graphs that model malware behaviour as data flows between system resources caused by issued system calls. We show that FrankenMods are substantially more robust and effective than a state-of-the-art graph metric-based detection approach.",
• notes = "Also known as \cite{7907008}",

}

Genetic Programming entries for Tobias Wuchner Martin Ochoa Enrico Lovat Alexander Pretschner

Citations