Harold Rivas – Chief Information Security Officer at Trellix, discusses the role of generative AI in cybersecurity, focusing on Trellix's adoption of AI for threat detection and model governance, while emphasizing the importance of privacy, responsible innovation, and cross-functional collaboration.Topics Include:Introduction to generative AI and its impact on cybersecurityHarold’s background in financial services and cybersecurity rolesTrellix’s focus on product feedback through the Customer Zero ProgramOverview of machine learning's role in anomaly detection at TrellixDevelopment of guided investigations to assist security operations teamsGenerative AI's growing importance in cybersecurity at TrellixLaunch of Trellix WISE at the RSA Conference in 2024Addressing the overload of security alerts with AI modelsIntegration of various AI models like Mistral and AnthropicReducing anomalies and workload for security operations teamsImportance of privacy in generative AI adoption and data governanceChallenges with GDPR and CPRA regulations in AI implementationFocus on privacy frameworks like the NIST Privacy FrameworkNeed for multi-stakeholder involvement in AI governanceDiscussion on model governance inspired by financial services practicesImportance of inventorying and testing AI models for securityBenefits of an AI Center of Excellence (AICOE) within organizationsModel governance in generative AI for regulatory and business outcomesThe impact of AI on labor, jobs, and decision-making processesAddressing cyber risk and threat modeling in AI environmentsThe double-edged sword of AI in offensive and defensive cybersecurityMITRE Atlas framework's role in AI-driven cybersecurity strategiesPotential negative consequences. Auto dealership hacked – Chevy Tahoe sold for $1Importance of vulnerability management and developer trainingEvolution of AI security tools and responsible use of generative AICollaboration, governance, and agility in AI adoption across organizationsQ&A 1: Outcomes and responsibilities an generative AI COE should have?Q&A 2: Model governance and financial implicationsQ&A 3: CISO response to model development, compliance and learning with customer dataQ&A 4: Thoughts and suggestions for rating systems for modelsQ&A 5: Selecting and evaluating modelsQ&A 6: Advice and experience for model deployment and technical controlsQ&A 7: Human reviewing AI responses to ensure accuracyQ&A 8: Will AI help avoid major outages in the future?Q&A 9: How to test and see maturity of models?Session wrap upParticipants:· Harold Rivas – CISO at TrellixSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

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