Abstract
Intrusion Detection System (IDS) has recently emerged as an important component for enhancing information system security. Data mining and machine learning technology has been extensively applied in network intrusion detection and prevention systems by discovering user behavior patterns from the network traffic data. In this paper, we propose a novel signature searching to detect intrusion based on data mining, which is an improved Apriori algorithm. We evaluate the capability of this new approach with the data from KDD 1999 data mining competition. Our experimental results demonstrate the potential of the proposed method.
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.
