Modeling, Measuring, and Mitigating Cybercrime

Attacks are becoming increasingly complex, and we therefore need more advanced techniques to model, detect, and predict such attacks. In this project we use cutting edge machine learning techniques to make sense of network attacks, developing prediction models and tools that allow us to better understand multi-step attacks.


ATTACK2VEC: Leveraging Temporal Word Embeddings to Understand the Evolution of Cyberattacks

Yun Shen and Gianluca Stringhini.
USENIX 2019.

Tiresias: Predicting Security Events Through Deep Learning

Yun Shen, Enrico Mariconti, Pierre-Antoine Vervier, and Gianluca Stringhini.
CCS, 2018.