KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Environmental Statistics Group
KAUST Grant NumberOSR-2015-CRG4-2582
Online Publication Date2019-02-28
Print Publication Date2018-11
Permanent link to this recordhttp://hdl.handle.net/10754/631694
MetadataShow full item record
AbstractCyber-attacks can seriously affect the security of computers and network systems. Thus, developing an efficient anomaly detection mechanism is crucial for information protection and cyber security. To accurately detect TCP SYN flood attacks, two statistical schemes based on the continuous ranked probability score (CRPS) metric have been designed in this paper. Specifically, by integrating the CRPS measure with two conventional charts, Shewhart and the exponentially weighted moving average (EWMA) charts, novel anomaly detection strategies were developed: CRPS-Shewhart and CRPS-EWMA. The efficiency of the proposed methods has been verified using the 1999 DARPA intrusion detection evaluation datasets.
CitationHarrou F, Bouyeddou B, Sun Y, Kadri B (2018) Detecting cyber-attacks using a CRPS-based monitoring approach. 2018 IEEE Symposium Series on Computational Intelligence (SSCI). Available: http://dx.doi.org/10.1109/SSCI.2018.8628797.
SponsorsThe research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST)Office of Sponsored Research (OSR) under Award No: OSR-2015-CRG4-2582. The anthors(Benamar Bouyeddou and Benamar Kadri) would like to thank the STIC Lab, Department of Telecommunications, Abou Bekr Belkaid University for the continued support during the research.
Conference/Event name8th IEEE Symposium Series on Computational Intelligence, SSCI 2018