Abstract:  Advanced Persistent Threat (ATP) continuously collects business processes and target systems of attack objects in advance by the way of multi-dimension, multi-stage and multi-object, and anonymously implements data theft of network space. The power network has the natural stability demand, it covers a wide range, involves large scale and has great loss after disaster. There exist the problems of the limited security domain of network node fragmentation and the dynamic detection of the whole domain feature in current APT attack predictions. In this paper, an ATP attack prediction model for power data network based on ant colony algorithm is proposed. By designing the global trusted system model of power network, we use manifold to spread the security boundary and link the fragmented nodes to ensure global security control. The time model of APT attack is built to realize the damage analysis of the attack to the trusted system. Attack prediction model is equivalent to ant colony pheromone, which realizes automatic tracking and adaptation of APT attack. The tests and simulations show that the new model improves prediction accuracy by 12.6%.

Key words: advanced persistent threat, security threat, attack prediction, ant colony algorithm