Pearson – Generative AI Security Conference
English | Tutorial | Size: 590.91 MB
Learn how to evaluate, deploy, and validate secure AI and LLM applications.
Insights and advice from industry leaders from Cisco, Robust Intelligence, and Microsoft.
Expert-led analyses of AI in cybersecurity covering topics from network security risks and AI-driven SOCs to the validation and security of Generative AI models.
Practical solutions for automated red-teaming, real-time validation techniques, and AI’s role in modern SOC environments.
Generative AI Security hosted by bestselling author and speaker Omar Santos offers the latest insights and strategies for securing AI and LLM applications, essential for anyone involved in cybersecurity, AI development, and experimentation.
This course has three core sections:
Is Your Network at Risk? How Can AI Help You?: Qihong Shao, Senior Manager and AI research scientist at Cisco’s ONEX AI group provides a comprehensive understanding of how AI-driven strategies can identify, assess, and mitigate network risks, thereby enhancing security postures.
Revolutionizing Cybersecurity with an AI-Driven SOC: Joseph Muniz, a member of Microsoft’s AI specialist team, focuses on the integration of AI in Security Operation Centers (SOCs) and explores how AI can address key SOC challenges. The session covers the incorporation of AI in modern SOC practices, including talent shortages, data and tool management, and achieving a unified perspective on incident management.
Validating Generative AI: How to Secure Your Models and Data: Kojin Oshiba, Co-Founder of Robust Intelligence, covers the security, ethical, and operational challenges of Generative AI applications highlighting associated risks and discriminative models while also proposing solutions like automated red-teaming and real-time validation for secure Gen AI usage in production environments.
Sections includes:
Segment 1: Is Your Network at Risk? How Can AI Help You?
Navigating the ever-evolving landscape of network security risks requires a nuanced and proactive approach. As network managers, you are tasked with the challenging role of safeguarding your environments against a myriad of threats that vary in complexity and scale. This essential session delves into:
– How cutting-edge AI innovations can be your strongest ally in this endeavor.
– The multifaceted nature of network risks and how AI-driven strategies can not only identify and assess these risks, but also offer robust, adaptive solutions for their minimization and mitigation.
– Equip you with the knowledge and insights needed to enhance the security posture of your network deployments through the integration of advanced AI technologies.
Qihong Shao, Senior Manager, AI research scientist, at Cisco’s ONEX AI group. She has a PhD in Computer Science, specialized in AI/ML. She has 13 years of industry experience in multiple IT companies (e.g., Microsoft, IBM T. J. Watson Research Center) as well as 30+ patents and 800+ paper citations.
Segment 2: Revolutionizing Cybersecurity with an AI-Driven SOC
This session will dive into practical applications of Artificial Intelligence in enhancing Security Operation Centers (SOCs). By concentrating on actionable insights and solutions, this talk aims to equip attendees with the knowledge to leverage AI in transforming SOC operations.
Participants will learn about:
– Integrating AI into SOC practices to improve efficiency and effectiveness.
– Addressing SOC’s top challenges, including staffing shortages, managing large datasets, and achieving a unified view of incidents.
– Implementing AI-driven strategies to proactively identify and mitigate security threats, enhancing overall cybersecurity posture.
Joseph Muniz is a security artificial intelligence specialist at Microsoft and a security researcher. He has extensive experience in designing security solutions and architecture as a trusted advisor for the top Fortune 500 corporations and US government. Joseph runs thesecurityblogger.com, a popular resource for security and product implementation. He is the author and contributor of several publications including titles ranging from security best practices to exploitation tactics. Joseph’s latest titles are The Modern Security Operations Center and The Zero Trust Network video course. When Joseph is not using technology, you can find him on the futbal field. Follow Joseph @SecureBlogger.
Segment 3: Validating Generative AI: How to Secure Your Models and Data
Generative AI applications are hard to produce and operate, mainly because it’s difficult to protect Gen AI against security, ethical, and operational risks. The enormous size of the input space and inherent complexity of third-party foundation models make this task more challenging than traditional ML models. Hence, a new paradigm is required to mitigate generative AI risk. In this session we will:
Summarize the new risks introduced by the new class of generative foundation models and applications through several examples.
Compare how these risks relate to the risks of mainstream discriminative models.
Discuss how a combined approach of automated red-teaming and real-time validation can give companies the confidence to securely use Gen AI in production at scale.
Kojin Oshiba is a co-founder of Robust Intelligence; an AI security startup offering a platform to automatically validate and protect AI applications. Kojin received his BA in Computer Science from Harvard prior to founding Robust Intelligence. He has also written multiple papers on AI security accepted to top AI conferences like ICML and NeurIPS. Kojin was named to the Forbes 30 Under 30 in 2023.
Who should take this course?
Cybersecurity professional or incident responder
CISO, manager, or IT security executive who needs to understand the impact of AI on your team and business
AI practitioner or enthusiast who wants to learn more about securing generative AI models and data.
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