October 28–31, 2019
Sean Park

Sean Park
Senior Malware Scientist, Trend Micro


Sean Park is a senior malware scientist in the Machine Learning Group at Trend Micro, as part of an elite team of researchers solving highly difficult problems in the battle against cybercrime. His main research focus is deep learning-based threat detection, including generative adversarial malware clustering, metamorphic malware detection using semantic hashing and Fourier transform, malicious URL detection with attention mechanism, macOS malware outbreak detection, semantic malicious script autoencoder, and heterogeneous neural networks for Android APK detection. Previously, he worked for Kaspersky, FireEye, Symantec, and Sophos. He also created a critical security system for banking malware at a top Australian bank.


5:00pm5:40pm Wednesday, October 30, 2019
Location: Grand Ballroom A/B
Sean Park (Trend Micro)
Average rating: *****
(5.00, 1 rating)
Practical defense systems require precise detection during malware outbreaks with only a handful of available samples. Sean Park demonstrates how to detect in-the-wild malware samples with a single training sample of a kind, with the help of TensorFlow's flexible architecture in implementing a novel variable-length generative adversarial autoencoder. Read more.
  • O'Reilly
  • TensorFlow
  • Google Cloud
  • IBM
  • Databricks
  • Tensor Networks
  • VMware
  • Amazon Web Services
  • One Convergence
  • Quantiphi
  • Lambda Labs
  • Tech Mahindra
  • cnvrg.io
  • Determined AI
  • Inferencery
  • Manceps, Inc.
  • PerceptiLabs
  • Valohai

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