Efficient and Secure Statistical DDoS Detection Scheme

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

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

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.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 3.138.69.101

In the current month:

Recent papers: 100 available of 100 total

2⁺ years older papers: 200 available of 200 total

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