Automatic Generation of Mobile Malwares Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Emre Aydogan and Sevil Sen",
  title =        "Automatic Generation of Mobile Malwares Using Genetic
  booktitle =    "18th European Conference on the Applications of
                 Evolutionary Computation",
  year =         "2015",
  editor =       "Antonio M. Mora and Giovanni Squillero",
  series =       "LNCS",
  volume =       "9028",
  publisher =    "Springer",
  pages =        "745--756",
  address =      "Copenhagen",
  month =        "8-10 " # apr,
  organisation = "EvoStar",
  keywords =     "genetic algorithms, genetic programming, Mobile
                 malware, Static analysis, Obfuscation, Evolutionary
  isbn13 =       "978-3-319-16548-6",
  URL =          "",
  DOI =          "doi:10.1007/978-3-319-16549-3_60",
  abstract =     "The number of mobile devices has increased
                 dramatically in the past few years. These smart devices
                 provide many useful functionalities accessible from
                 anywhere at anytime, such as reading and writing
                 e-mails, surfing on the Internet, showing facilities
                 nearby, and the like. Hence, they become an inevitable
                 part of our daily lives. However the popularity and
                 adoption of mobile devices also attract virus writers
                 in order to harm our devices. So, many security
                 companies have already proposed new solutions in order
                 to protect our mobile devices from such malicious
                 attempts. However developing methodologies that detect
                 unknown malwares is a research challenge, especially on
                 devices with limited resources. This study presents a
                 method that evolves automatically variants of malwares
                 from the ones in the wild by using genetic programming
                 (GP). We aim to evaluate the efficacy of current
                 anti-virus products, using static analysis techniques,
                 in the market. The experimental results show the
                 weaknesses of the static analysis tools available in
                 the market, and the need of new detection techniques
                 suitable for mobile devices.",
  notes =        "evoRISK EvoApplications2015 held in conjunction with
                 EuroGP'2015, EvoCOP2015 and EvoMusArt2015

Genetic Programming entries for Emre Aydogan Sevil Sen