Abstract
A post-processing filter is proposed to reduce false positives in network-based intrusion detection systems. The filter comprises three components, each one of which is based upon statistical properties of the input alert set. Special characteristics of alerts corresponding to true attacks are exploited. These alerts may be observed in batches, which contain similarities in the source or destination IPs, or they may produce abnormalities in the distribution of alerts of the same signature. False alerts can be recognized by the frequency with which their signature triggers false positives. The filter architecture and design are discussed. Evaluation results performed using the DARPA 1999 dataset indicate that the proposed approach can significantly reduce the number and percentage of false positives produced by Snort© ( Roesch, 1999). Our filter limited false positives by a percentage up to 75%.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
