2022
DOI: 10.31449/inf.v46i7.4033
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Detect and Mitigate Blockchain-Based DDoS Attacks Using Machine Learning and Smart Contracts

Abstract: The key target of Distributed Denial-of-Service (DDoS) attacks is to interrupt and suspend any available online services either executed for professional or personal gains. These attacks originate from the fast advancement in the number of insecure technologies. The attacks are caused due to the easy access to internet and advent of technology resulting to exponential growth of traffic volumes. DDoS attack remains most leading security risks to provisioning services. Also, the current embraced security mechani… Show more

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Cited by 3 publications
(1 citation statement)
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“…ML techniques are also beneficial in cybersecurity and can be used for defending against distributed denial-of-service (DDoS) attacks. Several ML-based approaches for identifying DDoS attacks have been proposed, including supervised, unsupervised, and hybrid approaches that combine the first two [44]. Another example is the project by Shahbazi and Byun [45], which aims to build a system for disaster management and emergency response based on social media platforms.…”
Section: Discussionmentioning
confidence: 99%
“…ML techniques are also beneficial in cybersecurity and can be used for defending against distributed denial-of-service (DDoS) attacks. Several ML-based approaches for identifying DDoS attacks have been proposed, including supervised, unsupervised, and hybrid approaches that combine the first two [44]. Another example is the project by Shahbazi and Byun [45], which aims to build a system for disaster management and emergency response based on social media platforms.…”
Section: Discussionmentioning
confidence: 99%