Extension of the Genetic Algorithm Based Malware Strategy Evolution Forecasting Model for Botnet Strategy Evolution Modeling
نویسندگان
چکیده
Botnets are considered to be among the biggest current threats to global IT infrastructure. Botnets are rapidly evolving and forecasting their survivability and propagation strategies is important for development of countermeasure techniques. Existing malware propagation models mainly concentrate on malware epidemic consequences modeling, i.e. forecasting the number of infected computers, simulating malware behavior or economic propagation aspects and are based only on current malware propagation strategies or oriented to other malware types. In this article we propose the botnet-oriented extension to our genetic algorithm based model, which aims at forecasting botnet propagation strategy evolution and may be used as a framework for other characteristics evolution forecasting. The efficiency of strategies is evaluated by applying the proposed fitness function. Genetic algorithm is selected as a modeling tool taking into consideration the efficiency of this method while solving optimization and modeling problems with large solution space. The main application of the proposed model framework is a countermeasures planning in advance and computer network design optimization.
منابع مشابه
Genetic Algorithm Modeling Approach for Mobile Malware Evolution Forecasting
Mobile malware is a relatively new but constantly increasing threat to information security and modern means of communication. Mobile malware evolution speedup is highly expected due to the increase of the SmartPhone and other mobile device market and malware development shift from vandalism to economic aspect. Forecasting evolution tendencies is important for development of countermeasure tech...
متن کاملGenetic algorithm based Internet worm propagation strategy modeling under pressure of countermeasures
Internet worms remain one of the major threats to the Internet infrastructure. Modeling allows forecasting the malware propagation consequences and evolution trends, planning countermeasures and many other tasks that cannot be investigated without harm to production systems in the wild. Existing malware propagation models mainly concentrate on malware epidemic consequences modeling, i.e. foreca...
متن کاملA Differential Evolution and Spatial Distribution based Local Search for Training Fuzzy Wavelet Neural Network
Abstract Many parameter-tuning algorithms have been proposed for training Fuzzy Wavelet Neural Networks (FWNNs). Absence of appropriate structure, convergence to local optima and low speed in learning algorithms are deficiencies of FWNNs in previous studies. In this paper, a Memetic Algorithm (MA) is introduced to train FWNN for addressing aforementioned learning lacks. Differential Evolution...
متن کاملA Novel Intelligent Energy Management Strategy Based on Combination of Multi Methods for a Hybrid Electric Vehicle
Based on the problems caused by today conventional vehicles, much attention has been put on the fuel cell vehicles researches. However, using a fuel cell system is not adequate alone in transportation applications, because the load power profile includes transient that is not compatible with the fuel cell dynamic. To resolve this problem, hybridization of the fuel cell and energy storage device...
متن کاملModified Pareto archived evolution strategy for the multi-skill project scheduling problem with generalized precedence relations
In this research, we study the multi-skill resource-constrained project scheduling problem, where there are generalized precedence relations between project activities. Workforces are able to perform one or several skills, and their efficiency improves by repeating their skills. For this problem, a mathematical formulation has been proposed that aims to optimize project completion time, reworki...
متن کامل