IP prefix hijacking remains a serious security threat to the traditional services in the Internet. It also harms the confidentiality and integrity of user data in Internet-enabled cloud services because of its great dependence on Internet routing infrastructure. In addition, collaborations between networks in the cloud environment, especially in cross-domain deployment, bring about new types of prefix hijacking attack, which may cause greater impact due to side-effect of the cooperation of victim and infected autonomous systems. It is important to understand what impact a prefix hijacking attack can cause and how the number and locations of participants can affect the attacking results. In this paper, we model this problem as an attack planning task and solve it by applying a genetic algorithm. By analyzing the best solution to the problem, we find that the type of victims plays a more important role in IP prefix hijacking than that of attackers. Attackers can gain great impact even when the prefixes of a small number of victims are hijacked. For attack planning, the degree of an autonomous system is a major criterion to be considered. These findings are useful for securing cloud computing networks by preventing and eliminating IP prefix hijacking attacks. Copyright © 2013 John Wiley & Sons, Ltd.