DMCA
Evolvable Malware
| Citations: | 4 - 0 self |
BibTeX
@MISC{Noreen_evolvablemalware,
author = {Sadia Noreen and Shafaq Murtaza and M. Zubair Shafiq and Muddassar Farooq},
title = {Evolvable Malware},
year = {}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
The concept of artificial evolution has been applied to numerous real world applications in different domains. In this paper, we use this concept in the domain of virology to evolve computer viruses. We call this domain as “Evolvable Malware”. To this end, we propose an evolutionary framework that consists of three modules: (1) a code analyzer that generates a high-level genotype representation of a virus from its machine code, (2) a genetic algorithm that uses the standard selection, cross-over and mutation operators to evolve viruses, and (3) the code generator converts the genotype of a newly evolved virus to its machinelevel code. In this paper, we validate the notion of evolution in viruses on a well-known virus family, called Bagle. The results of our proof-of-concept study show that we have successfully evolved new viruses–previously unknown and known-variants of Bagle–starting from a random population of individuals. To the best of our knowledge, this is the first empirical work on evolution of computer viruses. In future, we want to improve this proof-of-concept framework into a full-blown virus evolution engine.
Keyphrases
evolvable malware computer virus standard selection well-known virus family machine code genetic algorithm numerous real world application code generator high-level genotype representation different domain mutation operator proof-of-concept study show proof-of-concept framework random population new virus evolutionary framework code analyzer full-blown virus evolution engine artificial evolution first empirical work machinelevel code
