Abstract
Due to the developemt in the latest digital technologies, internet service use has surged recently. In order for these online businesses to succeed, they must be able to consistently and effectively supply their services. As a result of the DDoS assault, online sources are impacted in terms of both their availability and their computational capacity. DDoS attacks are useful for cyber-attackers since there is no effective techniqque for the identification of them. In recent years, researchers have been experimenting with duffernet latest techniques like machine learning (ML) approaches to see whether they can build effective methods for detecting DDoS assaults. Machine learning and big data are used to identify DDoS assaults in this research paper.
| Original language | English |
|---|---|
| Journal | CEUR Workshop Proceedings |
| Volume | 3080 |
| Publication status | Published - 2021 |
| Event | 2021 International Conference on Smart Systems and Advanced Computing, SysCom 2021 - Virtual, New Delhi, India Duration: 26 Dec 2021 → 27 Dec 2021 |
Keywords
- Big data
- DDoS attack
- Machine learning
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