Building a Benign Data Set

Explore the challenges and pitfalls of building benign data sets for machine learning in cybersecurity through this insightful conference talk from BSidesLV 2017. Delve into key takeaways, machine learning examples, and common biases such as selection, capture, negative set, and category bias. Examine prior work, including CSET 2009, and various sources of bias affecting data set creation. Gain valuable knowledge on constructing effective benign data sets and understand their importance in developing robust machine learning models for cybersecurity applications.

Introduction
Key Takeaways
Machine Learning
Machine Learning Example
Favorite Pitfalls
Selection Bias
Capture Bias
Negative Set Bias
Category Bias
Prior Work
CSET 2009
Sources of Bias
The Data Set
Other Sources
Conclusion