A Study On The Mechanism Of Immune Response Based Access Control

With regard to the problem that the efficiency of the classical multi-policies supporting mechanism, namely the generalized framework for access control (GFAC), markedly declines after enforcing several policy modules, a novel access control framework based on immunity is constructed with employing multiple principles and mechanisms of the artificial immune system to access control. It consults the learning, recognition and memory capabilities and distribution, self-organization and diversity characteristics of AIS.Firstly, the structure and access control process of the model is described and the elements are defined; secondly, the definition of antigen and antibody, data processing, the producing of mature cell and memory cell are given by combining the discipline of actual access requesting with the characteristic of immune system; lastly, access control decision-making is expounded in detail. In this part, based on the fact that the efficiency of GFAC is reduced due to frequently accessing ACI when making decision, immune response is introduced to the model. Several latent immune mechanisms realized the decision-making portion are well researched including the realization of the immune recognition, the immune learning, the immune memory and the dynamic updating and the interrelated algorithms.From the experiments, IGFAC is better than GFAC in time efficiency, because that IGFAC not only save the decision result and decrease the time accessing ACI, but also remember the continually visiting and respond in faster speed. With the simulation research and many experiments, it shows that IGFAC is able to improve the performance of the original GFAC, and especially, it has some capabilities of self-adaptive and diversity behaviors, which is the condition for the popularization of this model.