Towards Automated Malware Creation: Code Generation and Code Integration

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@TechReport{Cani:2014:SACtr2,
  author =       "A. Cani and M. Gaudesi and E. Sanchez and 
                 G. Squillero and A. Tonda",
  title =        "Towards Automated Malware Creation: Code Generation
                 and Code Integration",
  institution =  "Electronic CAD and Reliability Group, Department of
                 Control and Computer Engineering (DAUIN) of Politecnico
                 di Torino",
  year =         "2014",
  type =         "Internal Report",
  address =      "Corso Duca degli Abruzzi, 24, 10129 Turin, Italy",
  month =        "25 " # jan,
  keywords =     "genetic algorithms, genetic programming, MicroGP",
  true_link =    "http://www.cad.polito.it/downloads/White_papers/Towards%20Automated%20Malware%20Creation%20-%20Code%20Generation%20&%20Code%20Integration.pdf",
  URL =          "http://www.cad.polito.it/2014/Cani_2014_SACtr2.pdf",
  size =         "13 pages",
  abstract =     "The analogies between computer malware and biological
                 viruses are more than obvious. The very idea of an
                 artificial ecosystem where malicious software can
                 evolve and autonomously find new, more effective ways
                 of attacking legitimate programs and damaging sensitive
                 information is both terrifying and fascinating. The
                 paper proposes two different ways for exploiting an
                 evolutionary algorithm to devise malware: the former
                 targeting heuristic-based anti-virus scanner; the
                 latter optimizing a Trojan attack. Testing the
                 stability of a system against attacks, or checking the
                 reliability of the heuristic scan of anti-virus
                 software could be interesting for the research
                 community and advantageous to the IT industry.
                 Experimental results shows the feasibility of the
                 proposed approaches on simple real-world test cases. A
                 short paper on the same subject appeared at the 29th
                 Symposium On Applied Computing (SAC'14).",
  notes =        "Cites \cite{Sanchez:uGP:book} and
                 \cite{squillero:2005:GPEM}

                 Long version of 2 page poster at SAC 2014.

                 Orginally 3 Dec 2013 \cite{Cani:2014:SACtr} To avoid
                 overlap URL Cani_2014_SACtr2.pdf refers to January 25,
                 2014 version.",
}

Genetic Programming entries for A Cani Marco Gaudesi Ernesto Sanchez Giovanni Squillero Alberto Tonda

Citations