Extracting Low-Rate DDoS Attack Characteristics: The Case of Multipath TCP-Based Communication Networks

Author:

Lei Gang1ORCID,Ji Lejun1ORCID,Ji Ruiwen1ORCID,Cao Yuanlong1ORCID,Shao Xun2ORCID,Huang Xin1ORCID

Affiliation:

1. School of Software, Jiangxi Normal University, Nanchang 330022, China

2. School of Regional Innovation and Social Design Engineering, Kitami Institute of Technology, Japan

Abstract

The multipath TCP (MPTCP) enables multihomed mobile devices to realize multipath parallel transmission, which greatly improves the transmission performance of the mobile communication network. With the rapid development of all kinds of emerging technologies, network attacks have shown a trend of development with many types and rapid updates. Among them, low-rate distributed denial of service (LDDoS) attacks are considered to be one of the most threatening issues in the field of network security. In view of the current research status, by using the network simulation software NS2, this paper first compares and analyzes the throughput and delay performance of the MPTCP transmission system under LDDoS attacks and, further, conducts simulation experiments and analysis on the queue occupancy rate of the LDDoS attack flow to extract the basic attack characteristics of the LDDoS attacks. The experimental results show that the LDDoS attacks will have a major destructive effect on the throughput performance and delay performance of the MPTCP transmission system, resulting in a decrease in the robustness of the transmission system. By analyzing and comparing the occupancy rate of the LDDoS attack flow in the MPTCP transmission system, it can be concluded that (1) the occupancy rate of the LDDoS scattered pulse traffic sent by each puppet machine changes slightly, and (2) the occupancy rate of LDDoS attack data flow is much greater than that of ordinary TCP data flow.

Funder

Tohoku University

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Machine Recognition of DDoS Attacks Using Statistical Parameters;Mathematics;2023-12-31

2. OPNET Insights: Unpacking DDoS Effects on Network Performance;2023 5th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N);2023-12-15

3. An RF-based Low Rate DDoS Attack Real-time Detection System;2023 33rd International Telecommunication Networks and Applications Conference;2023-11-29

4. Online Machine Learning Approach to Detect and Mitigate Low-Rate DDoS Attacks in SDN-Based Networks;2023 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET);2023-09-12

5. GASF-IPP: Detection and Mitigation of LDoS Attack in SDN;IEEE Transactions on Services Computing;2023-09

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