LDoS Attack Detection System Based on ACO-LightGBM

Software Defined Network (SDN) is a new architecture that separates the data layer from the control layer.However, this architecture of SDN is not enough to resist all denial of service attacks. For example, low-rate denial of service attacks (LDoS) are periodic, low-rate, and very hidden. To solve...

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Bibliographic Details
Published in2024 3rd International Conference on Artificial Intelligence and Computer Information Technology (AICIT) pp. 1 - 4
Main Authors Li, Quli, Cheng, Li, Deng, Jialun
Format Conference Proceeding
LanguageEnglish
Published IEEE 20.09.2024
Subjects
Accuracy
ACO-LightGBM
Ant colony optimization
Artificial intelligence
Classification algorithms
Computer architecture
Information technology
LDoS attack detection
Real-time systems
Resists
SDN
Software defined networking
Technological innovation
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Summary:Software Defined Network (SDN) is a new architecture that separates the data layer from the control layer.However, this architecture of SDN is not enough to resist all denial of service attacks. For example, low-rate denial of service attacks (LDoS) are periodic, low-rate, and very hidden. To solve this problem, this paper designs a real-time attack detection system on the SDN architecture. LightGBM optimized by Ant Colony Optimization (ACO-LightGBM) is a primary tool for LDoS attack detection, and Mininet is used to simulate the real LDoS attack environment. Experiments show that LightGBM optimized by ant colony algorithm has the best detection performance compared with several other classifiers.
DOI:10.1109/AICIT62434.2024.10730475