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Applying ML to Cybersecurity

Image of Yaoshiang Ho
Yaoshiang Ho

Building Things with Machine Learning is Masterful AI's podcast covering interesting applications of machine learning. We started this podcast to focus less on innovative research, and more on the innovative ways ML is being applied to building products. 

In this episode, we speak with Yihua Liao to learn about how ML is used in cybersecurity. Yihua is Head of Data Science at Netskope, a next generation cybersecurity product, and CV and NLP are at the heart of many of its unique capabilities. Learn tips on how to think about recall and precision to increase product usage and challenges of working with Large Language Models (LLM). Yihua Liao’s PhD research was on security and machine learning, and he previously worked at Microsoft, Facebook, Uber, and his own startup.


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Key Moments: 

  • 03:44 - A unique application of Image Classification in cybersecurity: identifying sensitive documents like driver’s licenses so CISOs (chief information security officer) can set security rules for them.
  • 07:45 - Challenges of building Image Classifiers #1: High quality data.
  • 08:45 - Challenges of building Image Classifiers #2: Managing false positive and false negatives (recall and precision).
  • 09:15 - Challenges of building Image Classifiers #3: Managing latency (15 ms) for a real-time use case.
  • 10:38 - An application of NLP (natural language processing) in cybersecurity: classifying phishing websites.
  • 13:46 - Optimizing LLMs (Large Language Models) through quantization and distillation.
  • 14:45 - How Yihua got into ML.
  • 16:10 - How ML has evolved over the past 15 years.
Show Notes:

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