From Biological to Computational Arms Races -- Studying Cyber Security Dynamics
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InCollection{O'Reilly:2020:beacon,
-
author = "Una-May O'Reilly and Erik Hemberg",
-
title = "From Biological to Computational Arms Races --
Studying Cyber Security Dynamics",
-
booktitle = "Evolution in Action: Past, Present and Future: A
Festschrift in Honor of Erik D. Goodman",
-
publisher = "Springer",
-
year = "2020",
-
editor = "Wolfgang Banzhaf and Betty H. C. Cheng and
Kalyanmoy Deb and Kay E. Holekamp and Richard E. Lenski and
Charles Ofria and Robert T. Pennock and
William F. Punch and Danielle J. Whittaker",
-
series = "Genetic and Evolutionary Computation book series",
-
chapter = "27",
-
pages = "409--422",
-
keywords = "genetic algorithms, genetic programming, arms race,
dynamics, cyber security, adversarial coevolution,
Distributed Denial of Service, coevolutionary
algorithm, network, peer-2-peer, decision support,
grammar",
-
isbn13 = "978-3-030-39833-0",
-
DOI = "doi:10.1007/978-3-030-39831-6_27",
-
abstract = "The design of computational arms races can draw upon
the compelling inspiration of biological arms races. To
study cyber security attack-defense dynamics, we have
abstracted a description of biological adversarial
ecosystems to design an adversarial computational
system. The system has elements and processes with
abstracted biological analogs. It centers on
engagements. Engagements feature adversarial actors
(predator/attacker, prey/defender) competing with
conflicting objectives culminating in a measurable
performance-based outcome. Adversarial dynamics are
controlled by coevolution, which selects for better
adversaries over multiple engagements using aggregate
engagement performance as fitness. Altogether, this
system abstracted from nature is capable of
population-based, arms race dynamics arising from
interacting, evolving adversaries.",
-
notes = "GP?",
- }
Genetic Programming entries for
Una-May O'Reilly
Erik Hemberg
Citations