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A Hybrid Deep Learning and Blockchain Framework for Mitigating Distributed Denial-of-Service Attacks

Publicado
Servidor
Preprints.org
DOI
10.20944/preprints202512.0440.v1

This report mainly focuses on researching, identifying and analysing popular cyber attacks affecting individuals and organisations worldwide. Our group is needed to research about theselected cyberattack, Distributed Denial-of-Service(DDoS) background, recent relatedcyberattack cases, and reasons for getting attacked and think about the series of countermeasures to enhance the security measurement and prevent it from happening again. After thorough research, our group found that DDoS attack is one of the most unpreventable because it exploits weaknesses of the network topologies and standard protocols which makes it very difficult to prevent, hackers just have to overwhelm the system server. Thus, we think of implementing a “dynamic network traffic analysis and adaptive filtering system” and “blockchain-based traffic authentication” to enhance the security measures. Both systems are effective in filtering flooded traffic packages sent by non-human devices from overwhelming the server’s resources.

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