Spectrum Framework for ML-Based Threat Monitoring

Introduces the Spectrum framework for deploying and operationalizing machine learning models in threat monitoring pipelines.

Summary

This DEF CON talk covers spectrum framework for ml-based threat monitoring.

Nahid Farhady

Examines privacy-preserving machine learning techniques, homomorphic encryption, and differential privacy safeguards.

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Journal Club Live

Discusses practical methodologies for discovering exploitable bugs, implementation flaws, and attack surfaces in ML systems.

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Erick Galinkin

A primer breaking down core vocabulary, concepts, and foundational theory in machine learning security.

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