Abstract
One of the major security issues in cloud computing is to protect against network intrusions that affect confidentiality, availability and integrity of Cloud resources and offered services. To address this issue, we design and integrate Bayesian Classifier and Snort based network intrusion detection system (NIDS) in Cloud. This framework aims to detect network intrusions in Cloud environment with low false positives and affordable computational cost. To ensure feasibility of our NIDS module in Cloud, we evaluate performance and quality results on KDD'99 experimental dataset.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: 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.