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- Title
MALICIOUS BOTNET SURVIVABILITY MECHANISM EVOLUTION FORECASTING BY MEANS OF A GENETIC ALGORITHM.
- Authors
Goranin, Nikolaj; Čenys, Antanas; Juknius, Jonas
- Abstract
Botnets are considered to be among the most dangerous modern malware types and the biggest current threats to global IT infrastructure. Botnets are rapidly evolving, and therefore forecasting their survivability strategies is important for the development of countermeasure techniques. The article proposes the botnet-oriented genetic algorithm based model framework, which aimed at forecasting botnet survivability mechanisms. The model may be used as a framework for forecasting the evolution of other characteristics. The efficiency of different survivability mechanisms is evaluated by applying the proposed fitness function. The model application area also covers scientific botnet research and modeling tasks.
- Subjects
MALWARE; INFORMATION technology; GENETIC algorithms; MATHEMATICAL models; COMBINATORIAL optimization
- Publication
Science: Future of Lithuania / Mokslas: Lietuvos Ateitis, 2012, Vol 4, Issue 1, p13
- ISSN
2029-2341
- Publication type
Article
- DOI
10.3846/mla.2012.04