Search Results for author: Marc Frappier

Found 3 papers, 2 papers with code

Robustness Evaluation of Deep Unsupervised Learning Algorithms for Intrusion Detection Systems

1 code implementation25 Jun 2022 D'Jeff Kanda Nkashama, Arian Soltani, Jean-Charles Verdier, Marc Frappier, Pierre-Martin Tardif, Froduald Kabanza

Our experiments suggest that the state-of-the-art algorithms used in this study are sensitive to data contamination and reveal the importance of self-defense against data perturbation when developing novel models, especially for intrusion detection systems.

Anomaly Detection Data Poisoning +1

A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection Algorithms

1 code implementation21 Apr 2022 Maxime Alvarez, Jean-Charles Verdier, D'Jeff K. Nkashama, Marc Frappier, Pierre-Martin Tardif, Froduald Kabanza

Anomaly detection has many applications ranging from bank-fraud detection and cyber-threat detection to equipment maintenance and health monitoring.

Fraud Detection Unsupervised Anomaly Detection

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