The most significant risk to the development of a machine-learning-based threat detection tool is the Big Data processing required for maturity. Machine learning models often require large datasets to train effectively, and processing and analyzing this data can be time-consuming and resource-intensive. This can delay the development timeline, especially in a rapid CI/CD pipeline environment where timely delivery is crucial.
CASP+ highlights the challenges associated with machine learning and Big Data in security tool development, particularly the resource demands and the need for extensive data to ensure accuracy and maturity.
References:
* CASP+ CAS-004 Exam Objectives: Domain 2.0 - Enterprise Security Operations (Big Data and Machine Learning Challenges)
* CompTIA CASP+ Study Guide: Implementing and Managing Machine Learning in Security Environments