Type
Conference PaperKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionEnvironmental Statistics Group
Statistics Program
KAUST Grant Number
OSR-2015-CRG4-2582Date
2019-02-28Online Publication Date
2019-02-28Print Publication Date
2018-11Permanent link to this record
http://hdl.handle.net/10754/631694
Metadata
Show full item recordAbstract
Cyber-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.Citation
Harrou 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.Sponsors
The 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 name
8th IEEE Symposium Series on Computational Intelligence, SSCI 2018Additional Links
https://ieeexplore.ieee.org/document/8628797ae974a485f413a2113503eed53cd6c53
10.1109/SSCI.2018.8628797