Mitigating DDoS Attacks: A Text-Mining Approach Completed Research

In this study, we aim to assess and mitigate cyber-risk emanating for wrongly identifying critical themes in news articles about DDoS attacks by computing the probability of misclassification and expected losses associated with them. We use a hybrid approach comprising Latent Dirichlet Allocation and Kernel Naive Bayes classifier to ascertain the questions above. Subsequently, we suggest ways to mitigate cyber-risk by accepting, reducing, or passing it. Our study aims to help CTOs decide the best strategy to handle cyber-risk due to delayed response due to misidentifying critical themes.