SecAppDev 2023 - Machine learning security
SecAppDev 2023 offers three days of in-depth lectures and two days of hands-on workshops. Use the buttons below to navigate between the topics. The full schedule shows all sessions.
Machine learning security
Threat modeling
OWASP top 10
Authentication
Authorization
Architecture
Secure Coding
Supply chain security
API security
Web security
Cryptography
Security engineering for machine learning
Keynote lecture by Gary McGraw in room Lemaire
Monday June 12th, 09:15 - 10:30
How can the adoption of machine learning introduce systematic risk into our applications? This session discusses the results of applying architectural risk analysis to identify the top risks in engineering ML systems.
Key takeaway: The results of an architectural risk analysis (sometimes called a threat model) of ML systems, including the top five (of 78 known) ML security risks
Attacks against machine learning pipelines
Introductory lecture by Davy Preuveneers in room West Wing
Wednesday June 14th, 09:00 - 10:30
This session will explore various attacks against machine learning pipelines and their life cycle, present countermeasures and discuss best practices to make your ML models more robust in adversarial settings.
Key takeaway: ML adds value to applications but also increases the attack surface, imposing a holistic approach to secure the ML pipeline and lifecycle