Holistic and proactive machine learning approaches to predict cyberattacks in blockchain networks
Researchers have developed a machine learning framework designed to predict and defend against cyberattacks in blockchain networks. The system uses a Hawkes process to model attack patterns and a ResNet-based predictor to optimize network security.
Why it matters
As blockchain adoption grows, proactive security frameworks are essential to prevent large-scale financial and data breaches.
Scientific Reports ( 2026 ) Cite this article
We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply.
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