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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 cybersecurity
• Harold’s background in financial services and cybersecurity roles
• Trellix’s focus on product feedback through the Customer Zero Program
• Overview of machine learning's role in anomaly detection at Trellix
• Development of guided investigations to assist security operations teams
• Generative AI's growing importance in cybersecurity at Trellix
• Launch of Trellix WISE at the RSA Conference in 2024
• Addressing the overload of security alerts with AI models
• Integration of various AI models like Mistral and Anthropic
• Reducing anomalies and workload for security operations teams
• Importance of privacy in generative AI adoption and data governance
• Challenges with GDPR and CPRA regulations in AI implementation
• Focus on privacy frameworks like the NIST Privacy Framework
• Need for multi-stakeholder involvement in AI governance
• Discussion on model governance inspired by financial services practices
• Importance of inventorying and testing AI models for security
• Benefits of an AI Center of Excellence (AICOE) within organizations
• Model governance in generative AI for regulatory and business outcomes
• The impact of AI on labor, jobs, and decision-making processes
• Addressing cyber risk and threat modeling in AI environments
• The double-edged sword of AI in offensive and defensive cybersecurity
• MITRE Atlas framework's role in AI-driven cybersecurity strategies
• Potential negative consequences. Auto dealership hacked – Chevy Tahoe sold for $1
• Importance of vulnerability management and developer training
• Evolution of AI security tools and responsible use of generative AI
• Collaboration, governance, and agility in AI adoption across organizations
• Q&A 1: Outcomes and responsibilities an generative AI COE should have?
• Q&A 2: Model governance and financial implications
• Q&A 3: CISO response to model development, compliance and learning with customer data
• Q&A 4: Thoughts and suggestions for rating systems for models
• Q&A 5: Selecting and evaluating models
• Q&A 6: Advice and experience for model deployment and technical controls
• Q&A 7: Human reviewing AI responses to ensure accuracy
• Q&A 8: Will AI help avoid major outages in the future?
• Q&A 9: How to test and see maturity of models?
• Session wrap up

Participants:

· Harold Rivas – CISO at Trellix

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Register here for AWS re:Invent 2024, Dec 2-6, Las Vegas, NV

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Executive leaders from Arctic Wolf, Docker and Illumio share insights on fostering a strong security culture, balancing innovation with security, and addressing challenges in data protection and AI model development.

Topics Include:

• Overview of security culture in different company teams
• Importance of guidelines and secure IT infrastructure for AI models
• Challenges of accessing customer data while maintaining security
• Need for anonymization in early AI model development
• Docker's open-source ecosystem and security integration
• Dogfooding own products to ensure product reliability and trustworthiness
• Illumio’s high customer trust and responsibility for strong security practices
• Balancing security awareness with development speed at Illumio
• Gamifying security training to increase awareness
• Interlocking with customers to enhance security understanding for developers
• Embedding security into the development process from the start
• Illumio's approach to security in agile, cloud-native development
• Adapting customer success strategies for evolving security needs
• Rise of non-developers using AI in enterprises
• Educating business leaders on security best practices
• Scaling customer enablement and education through community engagement
• Challenges of placing security responsibilities in the developer workflow
• Arctic Wolf’s AI strategy for secure development
• Use of anonymized data in secure AI model training
• Generative AI’s potential to augment human creativity and efficiency
• Panelists' views on private AI and segmented model development
• Measuring security culture progress with gamification and development metrics
• Addressing human factors in cybersecurity and social engineering threats
• Emphasizing resiliency and containment in preventing widespread cyberattacks.
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Participants:

• Dean Teffer – Vice President of Artificial Intelligence, Arctic Wolf
• Dixie Dunn – VP of Customer Success, Docker
• Mario Espinoza – Chief Product Officer, Illumio
• Brian Shadpour – General Manager, AWS

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Register here for AWS re:Invent 2024, Dec 2-6, Las Vegas, NV

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Hear the generative AI journeys of Cohere, Epiq, and Forcura, including their market assessments, use case prioritization, responses to ethical and security considerations, while discussing generative AI's impact on healthcare, legal industries, and business applications.

Topics Include:

• Panel Introductions by David Cristini
• Where is Focura at in their AI journey
• Summary of Epiq’s AI journey to date
• Cohere’s AI journey to date
• Where did each company begin and assessing the market opportunities
• Prioritizing of use cases for Epiq
• Focura’s quick focus and results with generative AI
• Simplifying healthcare and improving patient experience with generative AI
• How do experiments and proof of concepts develop into production?
• Indicators that Cohere uses to identify customers ready to move fast
• Usecases that allows Forcura customers to move forward
• Guidance on engaging the Executive Team – getting Executive alignment
• How are legal and healthcare customers responding to AI solutions and challenges
• Changes of priority from customer advisory panels
• Evolving questions and concerns of functionality and data
• Some customers reporting AI evaluation is slowing them down
• Usecases that are easier to start off with to gain trust and traction
• Dealing with AI concerns of ethics, security and privacy – managing objections
• Understanding ethics concerns – privacy can often be about where data resides
• Customers often want “traceability”
• Accuracy and reducing hallucinations – AI comes with risk, business have to decide on business risk
• Future facing – what are we excited about?
• Generative AI is excellent at translation services – ROI is excellent
• Business applications and social impact of generative AI

Participants:

• MaryAnn Wofford – VP of Sales, Cohere
• Paul O'Hagan - Senior Director Product Management – AI Platform, Epiq
• Annie Mueller Erstling – COO, Forcura
• David Cristini - Director, ISV Sales North America, AWS

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