Efficient and Secure Statistical DDoS Detection Scheme

Hussein Majed; Hassan N. Noura; Ola Salman; Mohammad Malli; Ali Chehab

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Paper

Efficient and Secure Statistical DDoS Detection Scheme

Topics: Network Security

In Proceedings of the 17th International Joint Conference on e-Business and Telecommunications - Volume 1: WINSYS, 153-161, 2020 , Lieusaint - Paris, France

Authors: Hussein Majed ¹ ; Hassan N. Noura ² ; Ola Salman ³ ; Mohammad Malli ¹ and Ali Chehab ³

Affiliations: ¹ Arab Open University, Department of Computer Sciences, Beirut, Lebanon ; ² Arab Open University, Department of Computer Sciences, Beirut, Lebanon, American University of Beirut, Department of Electrical and Computer Engineering, Lebanon ; ³ American University of Beirut, Department of Electrical and Computer Engineering, Lebanon

Keyword(s): DDoS, Intrusion Detection, Traffic Aggregation, Network Security.

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.

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Paper citation in several formats:

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 - WINSYS; ISBN 978-989-758-445-9; ISSN 2184-3236, SciTePress, pages 153-161. DOI: 10.5220/0009873801530161

@conference{winsys20,
author={Hussein Majed. and Hassan N. 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 - WINSYS},
year={2020},
pages={153-161},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009873801530161},
isbn={978-989-758-445-9},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on e-Business and Telecommunications - WINSYS
TI - Efficient and Secure Statistical DDoS Detection Scheme
SN - 978-989-758-445-9
IS - 2184-3236
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
PB - SciTePress