RT Journal Article
T1 Adversarial Genetic Programming for Cyber Security: A Rising Application Domain Where GP Matters
A1 O'Reilly, Una-May
A1 Toutouh-el-Alamin, Jamal
A1 Pertierra, Marcos
A1 Prado, Daniel
A1 Garcia, Dennis
A1 Erb Luogo, Anthony
A1 Kelly, Jonathan
A1 Hemberg, Erik
K1 Programación genética (Informática)
AB Cyber security adversaries and engagements are ubiquitous and ceaseless. We delineate Adversarial Genetic Programming for Cyber Security, a research topic that, by means of genetic programming (GP), replicates and studies the behavior of cyber adversaries and the dynamics of their engagements. Adversarial Genetic Programming for Cyber Security encompasses extant and immediate research efforts in a vital problem domain, arguably occupying a position at the frontier where GP matters. Additionally, it prompts research questions around evolving complex behavior by expressing different abstractions with GP and opportunities to reconnect to the machine learning, artificial life, agent-based modeling and cyber security communities. We present a framework called RIVALS which supports the study of network security arms races. Its goal is to elucidate the dynamics of cyber networks under attack by computationally modeling and simulating them.
PB Springer
YR 2020
FD 2020-04
LK https://hdl.handle.net/10630/33878
UL https://hdl.handle.net/10630/33878
LA eng
NO O’Reilly, UM., Toutouh, J., Pertierra, M. et al. Adversarial genetic programming for cyber security: a rising application domain where GP matters. Genet Program Evolvable Mach 21, 219–250 (2020). https://doi.org/10.1007/s10710-020-09389-y
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026