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pww.comNVIDIA Corporation - Special Call - NasdaqGS:NVDA

NasdaqGS:NVDA

Pahal Patangia [Executives] 💬

Pahal Patangia provided insights on how NVIDIA Morpheus addresses cybersecurity challenges, particularly within the financial services industry. Here’s a detailed summary of his comments:

Introduction

  • Role and Background: Pahal Patangia leads developer relations for fintech and consumer finance at NVIDIA. He is responsible for growing the adoption of accelerated computing, machine learning, and data science within financial services.

Financial Services and Morpheus

  • Challenges in Financial Services:
    • Financial services handle a vast amount of personally identifiable information (PII), which must be kept secure.
    • Sensitive information is often the target in breaches, creating regulatory and customer satisfaction issues.
    • Remote working has increased the risk of sensitive information leaks due to compromised network security protocols.

Sensitive Information Detection

  • Importance:
    • 44% of breaches involve PII, causing significant regulatory and customer satisfaction problems.
    • Traditional methods are insufficient to protect sensitive information.
  • Morpheus Solution:
    • Morpheus offers a pre-built model for sensitive information detection.
    • Continuous updates improve the model’s performance, as evidenced by the increasing F1 scores.
    • Pre-built models and scripts enable users to assess and fine-tune the model’s performance on their own datasets.

Fraud Detection

  • Scale and Impact:
    • With 600 billion credit card transactions annually, fraud is a major concern.
    • Billions of dollars are anticipated to be lost to fraud in the coming years.
    • Rules-based and heuristics-based monitoring are reactive and insufficient.
  • Modern Techniques:
    • Advanced machine learning and deep learning algorithms, including graph neural networks, are essential for proactive fraud detection.
    • Graph embeddings help identify patterns in transactions, isolating fraudulent elements and reducing false positives.
    • This approach improves operational efficiency and customer satisfaction.

Ransomware Attacks

  • Impact:
    • Ransomware attacks cause delays in business operations and significant financial losses.
    • Traditional detection methods are not sophisticated enough to address the issue.
  • Morpheus and FinSec Lab Collaboration:
    • Morpheus, combined with BlueField DPUs, enabled a large credit card processor to detect ransomware attacks in seconds.
    • This allowed the isolation of infected servers to maintain business continuity and prevent further spread.

Conclusion

  • Engagement and Next Steps:
    • Pahal expressed interest in learning about attendees' use cases and how NVIDIA can help.
    • He invited participants to reach out via LinkedIn, email, or the chat to discuss further engagement opportunities.

Closing Remarks

  • Thank You:

    • Pahal thanked the audience for their participation and expressed interest in continuing the conversation to leverage NVIDIA’s accelerated computing platform for cybersecurity in financial services.

Killian Sexsmith [Executives] 💬

Killian Sexsmith provided extensive insights during the NVIDIA Corporation special call on July 12, 2023. Here’s a detailed summary of his statements:

  1. Introduction:

    • He introduced himself as the Segment Sales Lead for Morpheus, NVIDIA's cybersecurity solution, based in Austin, Texas.
    • He introduced Pahal Patangia, who leads developer relations for fintech and consumer finance at NVIDIA.

  2. Agenda:

    • He outlined the agenda, which included discussing cybersecurity challenges, the role of artificial intelligence in cybersecurity, Morpheus architecture, popular AI-driven use cases, and next steps for getting involved.

  3. Cybersecurity Challenges:

    • Data center traffic is rapidly increasing, with projections of 1 trillion connected devices, 5 billion internet users, and 221 zettabytes of data.
    • The cost of cyberattacks is growing, and Morpheus addresses this by providing insights into data using AI.

  4. Zero Trust Approach:

    • He discussed the importance of a zero-trust approach, emphasizing that perimeter security alone is not sufficient.
    • After authentication, behavior must be continuously validated to ensure that credentials have not been compromised.

  5. Morpheus Framework:

    • Morpheus is a lightweight framework deployable in the cloud, on-premises, or at the edge.
    • It allows enforcing zero-trust principles where needed, providing an early view of potential attacks.

  6. Data Problem:

    • Cybersecurity is fundamentally a data problem, with a high velocity of data streams and complex data.
    • AI helps in gaining better insights into data and is becoming essential due to attackers using AI in their strategies.

  7. Ecosystem Integration:

    • NVIDIA focuses on analyzing data, applying models, and providing acceleration.
    • Morpheus integrates with existing cybersecurity solutions to augment their capabilities.

  8. Architecture:

    • The architecture supports cloud, data center, edge, and embedded systems, requiring a GPU of Pascal or later.
    • Libraries such as RAPIDS, Cyber Log Accelerator, Triton Inference Server, and TensorRT are used, and Morpheus adds value as an abstraction layer.

  9. Data Agnosticism:

    • Morpheus is data-agnostic and can be integrated with various data sources.
    • Users can provide feedback on additional data sources for future integrations.

  10. Performance and Scale:

    • Morpheus offers a fast backbone built on a reactive framework and scales out using GPUs for parallelization.
    • This performance and scale are critical for achieving 100% visibility and analysis of incoming data.

  11. Development and Deployment:

    • Morpheus is packaged as a container or Kubernetes manifest, simplifying deployment.
    • The framework uses a simple API and CLI interface to ease the development process.

  12. Real-Time Telemetry:

    • Real-time telemetry provides early warnings with actionable alerts, separating signal from noise.
    • Integration with BlueField DPUs is optional but enhances capabilities, especially for ransomware detection.

  13. Use Cases:

    • He discussed several use cases, including credential attacks, digital fingerprinting, and phishing.
    • Digital fingerprinting involves detecting behavioral changes in user activity to identify anomalies.
    • Phishing attacks are growing in prominence due to advancements in AI, and Morpheus improves accuracy in detecting phishing emails.

  14. GenAI and Training:

    • NVIDIA is working on generating labeled data using Generative AI (GenAI) to improve model training.
    • The focus is on creating robust training data for models to identify attackers, especially in spear-phishing scenarios.

  15. Customer Stories:

    • He highlighted a partnership with Deloitte, which saw significant improvements in speed and cost savings using Morpheus.
    • Deloitte achieved 3x faster performance for lateral movement detection and 215x acceleration for zero-day detection.

  16. Getting Involved:

    • He encouraged attendees to participate in a free self-paced course and request a free workshop.
    • Morpheus can also be tried in LaunchPad, NVIDIA’s free service for short-term remote lab access.

  17. Closing:

    • He thanked the attendees and invited them to share their challenges and how NVIDIA could help.
    • He encouraged reaching out via LinkedIn or email for further discussions.

Throughout the presentation, Killian emphasized the importance of collaboration and feedback from the community to enhance Morpheus and address evolving cybersecurity threats.