A quantitative model of the security intrusion process based on attacker behavior

This paper is based on a conceptual framework in which security can be split into two generic types of characteristics, behavioral and preventive. Here, preventive security denotes the system's ability to protect itself from external attacks. One way to describe the preventive security of a system is in terms of its interaction with the alleged attacker, i.e., by describing the intrusion process. To our knowledge, very little is done to model this process in quantitative terms. Therefore, based on empirical data collected from intrusion experiments, we have worked out a hypothesis on typical attacker behavior. The hypothesis suggests that the attacking process can be split into three phases: the learning phase, the standard attack phase, and the innovative attack phase. The probability for successful attacks during the learning and innovative phases is expected to be small, although for different reasons. During the standard attack phase it is expected to be considerably higher. The collected data indicates that the breaches during the standard attack phase are statistically equivalent and that the times between breaches are exponentially distributed. This would actually imply that traditional methods for reliability modeling could be applicable