RESEARCH ON TECHNIQUES TO ENHANCE DDoS ATTACK PREVENTION USING CUMULATIVE SUM AND BACKPROPAGATION ALGORITHMS
This paper focuses on enhancing DDoS attack prevention capabilities through the combination of the Cumulative Sum (CUSUM) algorithm and the Backpropagation method, aiming to detect attack indicators early and accurately. The CUSUM algorithm is used to monitor and analyze network traffic over ti...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Trường Đại học Vinh
2024-12-01
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| Series: | Tạp chí Khoa học |
| Subjects: | |
| Online Access: | https://vujs.vn//api/view.aspx?cid=193f23b9-9933-45fc-aaa7-0a3e67177b60 |
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| Summary: | This paper focuses on enhancing DDoS attack prevention
capabilities through the combination of the Cumulative Sum
(CUSUM) algorithm and the Backpropagation method, aiming
to detect attack indicators early and accurately. The CUSUM
algorithm is used to monitor and analyze network traffic over
time, identifying unusual fluctuations in traffic without
requiring prior knowledge of attack types. Meanwhile, the
Backpropagation method is applied to optimize neural
networks, enabling the system to learn from previous traffic
data and distinguish clearly between legitimate traffic and
attack traffic. Compared to previous research methods, this
combined approach offers several significant advantages.
First, CUSUM provides high-accuracy attack detection,
allowing the system to respond promptly. Second,
Backpropagation enables the system to improve automatically
over time, reducing false alarm rates and enhancing prevention
effectiveness. Finally, the feasibility and effectiveness of the
solution are demonstrated through real-world experiments,
showing improved detection rates and faster response times
compared to traditional methods. |
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| ISSN: | 1859-2228 |