Abstract: In recent years,complex and diverse network attacks are led by increasing number of loopholes together with the continuous evolution of network intrusion methods and hacker techniques.However,the traditional attack tree model is difficult to be construct automatically,and its quality is highly dependent on analyst's expertise.Besides,it has some shortcomings in the expression about the relationship between attack intention and attack operation.In order to detect potential security threads to system assets with high quality and support the implementation of automatic detection,this paper proposes an anti-target attack tree model and its construction method based on the intention of attackers.Based on the attacker's intention,the model describes the attacker's attack process and target by iteratively decomposing the anti-target elements,and expresses it in the form of attack tree,so as to find the security problems of the system efficiently.Based on the Datalog language,a formal description of the decomposition strategy of the anti-target attack tree model is given and the inference rules are defined to provide support for the automatic construction of the anti-target attack tree model and the automatic detection of the attack risks.The method proposed in this paper is applied to real attack case scenarios for analysis,and the actual attack scenarios and potential security risks of the attacked system are successfully detected,which proves the effectiveness of the proposed method.

Key words: Aautomatic detection, Anti-target attack tree model, Attack strategy, Formal reasoning, Risk detection