چكيده به لاتين
One of the problems that we are faced today are the propagational epidemic phenomena, specially, malware propagation in large-scale networks. Attacking and penetrating to these systems through computer malware is vital and it could damage irrecoverable to people and organizations.
One of the most important properties of malware propagation in cyberspace is its large-scale nature. The usage of computer simulation for analyzing this phenomenon in large scale, is so important. Accessing to a simulator that resolves this issue is a great challenge. Flexibility for simulating different kinds of problems, ability to model different kinds of behaviors and agent-based perspective are the other requirements of this system.
Some simulators have been developed so far but, most of them do not meet the requirements and they do not have a general solution. Most of these simulations are limited to a specific model or they are specific to simulating the propagation phenomenon itself, and extra information cannot be considered. Because of the usage of centralized architecture and not supporting the distributed approach, they usually do not have very high performance and we cannot call them large-scale.
In this thesis, an agent-based, scalable, flexible and large-scale simulation architecture is proposed. It also has the ability to simulate most of the epidemic problems. In addition, a software system is developed based on this architecture for simulation of malware propagation. This software is able to simulate malware propagation with any epidemic model and different properties and produce graphical results dynamically. The software is evaluated through different experiments, the results of which are given in the thesis. The usage of real-world data, and the ability to model different phenomena are some innovations of this method.
