Our publication “Security Patterns for Machine Learning: The Data-Oriented Stages” is now available online. This is the work of PhD Student, Xinrui Zhang. This paper presents a collection of security patterns for the data-oriented stages in the machine learning (ML) workflow, including data collection, data storage, and data preparation. It provides a concise guidance on how to protect each stage from known threats, as well as a communication vocabulary for different roles to consider security without being security experts. The paper was presented at the 27th European Conference on Pattern Languages of Programs ( EuroPLoP 2022) in July 2022. See Publications for more details!
Home / Publication / New Publication: Security Patterns for Machine Learning: The Data-Oriented Stages
New Publication: Security Patterns for Machine Learning: The Data-Oriented Stages