Machine Learning for Security and Security for Machine Learning with Nicole Nichols - TWiML Talk #252
Published:Apr 16, 2019 17:01
•1 min read
•Practical AI
Analysis
This article summarizes a podcast episode featuring Nicole Nichols, a senior research scientist, discussing her presentation at GTC. The core focus is on the intersection of machine learning and security. The discussion covers two key use cases: insider threat detection and software fuzz testing. The article highlights the application of recurrent neural networks (RNNs), both standard and bidirectional, for identifying malicious activities. It also touches upon the use of deep learning to enhance software fuzzing techniques. The article promises a deeper dive into these topics, suggesting a practical application of AI in cybersecurity.
Key Takeaways
Reference
“The article doesn't contain a direct quote, but it discusses the content of a presentation.”