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Intrusion detection and/or prevention systems (IDPS) represent an important line of defense against the variety of attacks that can compromise the security and well functioning of an enterprise information system. IDPSes can be network or host-based and can collaborate in order to provide better detections of malicious traffic. Although several IDPS systems have been proposed, their appropriate configuration and control for effective detection and prevention of attacks has always been far from trivial. Another concern is related to the slowing down of system performance when maximum security is applied, hence the need to trade off between security enforcement levels and the performance and usability of an enterprise information system. In this paper we motivate the need for and present a policy-based framework for the configuration and control of the security enforcement mechanisms of an enterprise information system. The approach is based on dynamic adaptation of security measures based on the assessment of system vulnerability and threat prediction and provides several levels of attack containment. As an application, we have implemented a dynamic policy-based adaptation mechanism between the Snort signature-based IDPS and the light weight anomaly-based FireCollaborator IDS. Experiments conducted over the DARPA 2000 and 1999 intrusion detection evaluation datasets show the viability of our framework.