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.
Recommended Citation
Sharma, Kalpit and Mukhopadhyay, Arunabha, "Mitigating DDoS attacks: A Text-mining approach" (2021). AMCIS 2021 Proceedings. 10.
https://aisel.aisnet.org/amcis2021/adv_info_systems_general_track/adv_info_systems_general_track/10
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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