Efficient and Secure Statistical DDoS Detection Scheme

Hussein Majed, Hassan Noura, Ola Salman, Mohammad Malli, Ali Chehab

2020

Abstract

One of the hardest challenges in cybersecurity is the detection and prevention of Distributed Denial of Service (DDoS) attacks. In this paper, a lightweight statistical approach for DDoS detection is presented, in addition to preventive and corrective countermeasures. The proposed solution is designed to be applied at the Internet Service Provider (ISP) level. Based on aggregated NetFlow statistics, the proposed solution relies on the Z-score and co-variance measures to detect DDoS traffic as a deviation from normal traffic. The implementation results show a high detection rate (up to 100%) for 30 seconds time slot.

Paper Citation

in Harvard Style

Majed H., Noura H., Salman O., Malli M. and Chehab A. (2020). Efficient and Secure Statistical DDoS Detection Scheme.In Proceedings of the 17th International Joint Conference on e-Business and Telecommunications - Volume 1: WINSYS, ISBN 978-989-758-445-9, pages 153-161. DOI: 10.5220/0009873801530161

in Bibtex Style

@conference{winsys20,
author={Hussein Majed and Hassan Noura and Ola Salman and Mohammad Malli and Ali Chehab},
title={Efficient and Secure Statistical DDoS Detection Scheme},
booktitle={Proceedings of the 17th International Joint Conference on e-Business and Telecommunications - Volume 1: WINSYS,},
year={2020},
pages={153-161},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009873801530161},
isbn={978-989-758-445-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on e-Business and Telecommunications - Volume 1: WINSYS,
TI - Efficient and Secure Statistical DDoS Detection Scheme
SN - 978-989-758-445-9
AU - Majed H.
AU - Noura H.
AU - Salman O.
AU - Malli M.
AU - Chehab A.
PY - 2020
SP - 153
EP - 161
DO - 10.5220/0009873801530161