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From Replay to Regeneration: Recovery of UDP Flood Network Attack Scenario Based on SDN

Authors :
Yichuan Wang
Junxia Ding
Tong Zhang
Yeqiu Xiao
Xinhong Hei
Source :
Mathematics, Vol 11, Iss 8, p 1897 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

In recent years, various network attacks have emerged. These attacks are often recorded in the form of Pcap data, which contains many attack details and characteristics that cannot be analyzed through traditional methods alone. Therefore, restoring the network attack scenario through scene reconstruction to achieve data regeneration has become an important entry point for detecting and defending against network attacks. However, current network attack scenarios mainly reproduce the attacker’s attack steps by building a sequence collection of attack scenarios, constructing an attack behavior diagram, or simply replaying the captured network traffic. These methods still have shortcomings in terms of traffic regeneration. To address this limitation, this paper proposes an SDN-based network attack scenario recovery method. By parsing Pcap data and utilizing network topology reconstruction, probability, and packet sequence models, network traffic data can be regenerated. The experimental results show that the proposed method is closer to the real network, with a higher similarity between the reconstructed and actual attack scenarios. Additionally, this method allows for adjusting the intensity of the network attack and the generated topology nodes, which helps network defenders better understand the attackers’ posture and analyze and formulate corresponding security strategies.

Details

Language :
English
ISSN :
22277390
Volume :
11
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Mathematics
Publication Type :
Academic Journal
Accession number :
edsdoj.554f283bde78494bbda31954a009e48b
Document Type :
article
Full Text :
https://doi.org/10.3390/math11081897