Advances in Information Systems (General Track)

Paper Type

Complete

Paper Number

1419

Description

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 Naïve 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.

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Aug 9th, 12:00 AM

Mitigating DDoS attacks: A Text-mining approach

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 Naïve 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.

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