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Transformer Models for Network Traffic Analysis

While at JHU APL, I created transformer-based machine learning model for anomalous network traffic detection that yielded significantly higher accuracy than previous LSTM-based models.

I also deployed the machine learning models for anomalous network traffic detection to sponsor networks. I was responsible for troubleshooting software & the deployment to the sponsor network.

Additionally, I developed social media malware trend analysis by utilizing social media APIs to proactively identify specific malware likely to be in use.

This post is licensed under CC BY 4.0 by the author.