Securing the Software Development Life Cycle with Machine Learning

Explore how machine learning and natural language processing can enhance security in software development. Learn to identify and track security bugs throughout the software development life cycle, from basic concepts to practical implementation. Delve into handling challenges like mislabeled training data, privacy concerns, and deployment strategies. Gain insights into the role of data science in security, classification systems, and the impact of machine learning on bug detection. Discover the benefits for both security teams and customers, and understand the implications for developers and security practitioners in this comprehensive 44-minute conference talk from the RSA Conference.

Introduction
Mike the Developer
What happened
Agenda
The Basics
Two Main Camps
Level of Trust
Where do bugs go
How many bugs are there
What does this look like
Does this matter
Finding bugs
The opportunity for ML
How ML works
What does the security team want
What is supervised learning
Recap
Data
Data Science
Classification System
Data Science and Security
Data Quality
Takeaways
How does this help your customers
What this means to you
What this means to customers
What does this mean for you