[AI] security study plan

[carloscn]

Design and implement comprehensive security frameworks for AI/ML pipelines, from data ingestion through model deployment

Conduct security assessments of machine learning deployments, identifying vulnerabilities including adversarial attacks, data poisoning, and model inversion risks

Develop automated security testing and monitoring solutions for AI/ML systems at scale
Lead incident response for AI/ML security events, coordinating technical remediation and stakeholder communication

Establish secure MLOps practices, including secure model versioning, access controls, and audit trails

Collaborate with engineering teams to integrate security-by-design principles into AI/ML development workflows

Business & Strategic Leadership

Translate complex AI/ML security risks into business impact assessments for leadership and stakeholders

Develop and present security roadmaps that align with business objectives and product timelines
Lead cross-functional teams through security initiatives, fostering collaboration between engineering, legal, privacy, and product teams

Establish metrics and KPIs to measure AI/ML security posture and communicate progress to executives

[carloscn]

[carloscn]

https://github.com/Acmesec/theAIMythbook