The Use of Rules Engines in Cybersecurity Threat Detection
Jeremy discusses the effectiveness of rules engines in detecting threats in the cybersecurity field. He explains that rules are useful for encoding domain knowledge and providing protection, especially when there is limited data available about a new threat. The constantly evolving nature of the threat landscape in cybersecurity, as attackers adapt to new strategies, is also highlighted. He also notes that rules engines allow for quick adaptation to new threats before sufficient data is collected to train a model.
MLOps Coffee Sessions #134 with Jeremy Thomas Jordan, Building Threat Detection Systems: An MLE’s Perspective co-hosted by Vishnu Rachakonda.
Link to the full episode: https://youtu.be/13nOmMJuiAo
// Abstract
There is a clear pattern that we have been seeing with some of these greats in MLOps. So many use writing as a forcing function to learn about where they have holes in their understanding of something.
If you are not writing, this episode explains why writing is important for your own development. Jeremy goes into writing in depth as to how beneficial it is for him to write and for him to see that he doesn’t understand something if he cannot re-articulate it in writing.
// Bio
Jeremy is a machine learning engineer currently working at Duo Security where he focuses on building ML infrastructure to operate threat detection systems at scale. He previously worked at Proofpoint, where he built models for phishing and malware detection.
// MLOps Jobs board
https://mlops.pallet.xyz/jobs
// MLOps Swag/Merch
https://mlops-community.myshopify.com/
// Related Links
Website: https://www.jeremyjordan.me/
Normcore Conference: https://normconf.com/
Vicky Boykiss newsletters: https://vickiboykis.com/
Effective testing for machine learning systems blog post: https://www.jeremyjordan.me/testing-ml/
“The Cobbler’s Children Have No Shoes”: https://grammarhow.com/the-cobblers-children-have-no-shoes-meaning-origin/
Jeremy’s blogposts: https://ghost.org/
Variational autoencoders: https://www.jeremyjordan.me/variational-autoencoders/
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cyber security
