Effect of Learning and Database in Robustness of Security Tools Based on Immune System Modeling

Increasing complexity and dynamics of systems has reduced the efficiency of security tools. For overcoming this problem, security tools introduce newer patches, thereby the size of database and computation overloads are increased. By Biological Immune System (BIS) modeling andsimulation, its behavior in different situations will be considered and the effect of database size and learning ability in robustness of the BIS will be evaluated. For the BIS modeling and simulation, Biological Agent will be introduced and a Multi Agent System in Netlogo software has been designed. According the results of simulation, the effect of learning rate in different states in system's robustness has been evaluated. Furthermore, robustness of the systems with different sizes of database in the initial state has been considered. After all, the effectthese two parameters on the BIS robustness have been illustrated and compared.