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1
Introduction
2
Mike the Developer
3
What happened
4
Agenda
5
The Basics
6
Two Main Camps
7
Level of Trust
8
Where do bugs go
9
How many bugs are there
10
What does this look like
11
Does this matter
12
Finding bugs
13
The opportunity for ML
14
How ML works
15
What does the security team want
16
What is supervised learning
17
Recap
18
Data
19
Data Science
20
Classification System
21
Data Science and Security
22
Data Quality
23
Takeaways
24
How does this help your customers
25
What this means to you
26
What this means to customers
27
What does this mean for you
Description:
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.

Securing the Software Development Life Cycle with Machine Learning

RSA Conference
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