Detecting SYN flood attacks via statistical monitoring charts: A comparative study

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Type
Conference Paper
Authors
Bouyeddou, Benamar
Harrou, Fouzi cc
Sun, Ying cc
Kadri, Benamar
KAUST Department
Applied Mathematics and Computational Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Statistics Program
KAUST Grant Number
OSR-2015-CRG4-2582
Date
2017-12-14
Online Publication Date
2017-12-14
Print Publication Date
2017-10
Permanent link to this record
http://hdl.handle.net/10754/626839

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Abstract
Accurate detection of cyber-attacks plays a central role in safeguarding computer networks and information systems. This paper addresses the problem of detecting SYN flood attacks, which are the most popular Denial of Service (DoS) attacks. Here, we compare the detection capacity of three commonly monitoring charts namely, a Shewhart chart, a Cumulative Sum (CUSUM) control chart and exponentially weighted moving average (EWMA) chart, in detecting SYN flood attacks. The comparison study is conducted using the publicly available benchmark datasets: the 1999 DARPA Intrusion Detection Evaluation Datasets.
Citation
Bouyeddou B, Harrou F, Sun Y, Kadri B (2017) Detecting SYN flood attacks via statistical monitoring charts: A comparative study. 2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B). Available: http://dx.doi.org/10.1109/ICEE-B.2017.8192118.
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 authors (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.
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Journal
2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B)
DOI
10.1109/ICEE-B.2017.8192118
Additional Links
http://ieeexplore.ieee.org/document/8192118/
Collections
Conference Papers; Applied Mathematics and Computational Science Program; Statistics Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division